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8-21-2017

A Decision Making Tool for IncorporatingSustainability Measures in Rigid Pavement DesignNeveen Samy Talaat SolimanLouisiana State University and Agricultural and Mechanical College, novesol3@gmail.com

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Recommended CitationTalaat Soliman, Neveen Samy, "A Decision Making Tool for Incorporating Sustainability Measures in Rigid Pavement Design" (2017).LSU Doctoral Dissertations. 4098.https://digitalcommons.lsu.edu/gradschool_dissertations/4098

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A DECISION MAKING TOOL FOR INCORPORATING SUSTAINABILITY

MEASURES

IN RIGID PAVEMENT DESIGN

A Dissertation

Submitted to the Graduate Faculty of the

Louisiana State University and

Agricultural and Mechanical College

In partial fulfillment of the requirements of the

requirements for the degree of

Doctor of Philosophy

in

The Department of Construction Management

by

Neveen Samy Talaat Soliman

B.S., The American University in Cairo, 2011

M.S., The American University in Cairo, 2013

December 2017

ii

ACKNOWLEDGMENTS

First and foremost, my praises and thanks are to God, who provided me with the opportunity

to accomplish this work.

I would like to acknowledge the Louisiana Transportation and Research Center

(LTRC) for funding this work. I would also like to acknowledge and thank my advisor, Dr.

Marwa Hassan, who guided and helped me through this long journey. Thank you so much for

your continuous support. You have always been there for my questions, even when you were

very busy.

Finally, I would also like to thank my father, mother, sister, and grandparents who

have always been by my side. Thank you for all your continual and ceaseless support. You

always have motivated me in every step of my life. I would like to take this opportunity to

thank you. I could never have achieved this success without your encouragement and

inspiration.

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TABLE OF CONTENTS

ACKNOWLEDGMENTS........................................................................................................ii

DEFINITIONS..........................................................................................................................v

ABBREVIATIONS AND ACRONYMS................................................................................vii

ABSTRACT...............................................................................................................................x

CHAPTER 1. INTRODUCTION...............................................................................................1

1.1 PROBLEM STATEMENT AND RESEARCH QUESTIONS .................................. 5

1.2 GOAL AND OBJECTIVES ....................................................................................... 6

1.3 RESEARCH APPROACH AND IMPLEMENTATION ........................................... 7

1.4 CONTRIBUTION TO THE BODY OF KNOWLEDGE ......................................... 11

1.5 REFERENCES .......................................................................................................... 11

CHAPTER 2. LITERATURE REVIEW..................................................................................13

2.1 INTRODUCTION ..................................................................................................... 13

2.2 LIFECYCLE ASSESSMENT (LCA) ....................................................................... 14

2.3 PAVEMENT LIFECYCLE PHASES ....................................................................... 25

2.4 SUSTAINABILITY RATING TOOLS .................................................................... 69

2.5 ENVIRONMENTAL ASSESSMENT ...................................................................... 73

2.6 SOCIAL LIFECYCLE ASSESSMENT (SLCA) ..................................................... 75

2.7 PERFORMANCE ASSESSMENT MEASURES .................................................... 76

2.8 LIFECYCLE COST ANALYSIS (LCCA) ............................................................... 77

2.9 PAVEMENT DESIGN AND SUSTAINABILITY .................................................. 90

2.10 SUMMARY .............................................................................................................. 96

2.11 REFERENCES .......................................................................................................... 97

CHAPTER 3. NEW FRAMEWORK AND ASSOCIATED DATA COLLECTION

PROCESS...............................................................................................................................114

3.1 INTRODUCTION ................................................................................................... 114

3.2 EXISTING VS. PROPOSED PAVEMENT DESIGN FRAMEWORK ................ 114

3.3 MODULE 1: ENVIRONMENTAL DATA COLLECTION PROCESS ............... 119

3.4 MODULE 2: ECONOMIC IMPACT ..................................................................... 134

3.5 DISCOUNT RATE FOR LIFECYCLYE COST ANALYSIS ............................... 142

3.6 DATA OUTPUT FROM CHAPTER 3 .................................................................. 144

3.7 SUMMARY ............................................................................................................ 144

3.8 REFERENCES ........................................................................................................ 147

CHAPTER 4. IMPLEMENTATION.....................................................................................150

4.1 INTRODUCTION ................................................................................................... 150

4.2 ALTERNATIVE DESIGN COMPARISON MODULE ........................................ 150

4.3 SOFTWARE DEMONSTRATION ........................................................................ 173

4.4 STUDY SIGNIFICANCE: THE BIGGER PICTURE. HOW CAN THIS

FRAMEWORK BE USED IN THE REAL WORLD? .......................................... 181

4.5 SUMMARY ............................................................................................................ 184

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4.6 REFERENCES ........................................................................................................ 184

CHAPTER 5. DEMONSTRATION OF THE DEVELOPED FRAMEWORK IN CASE

STUDIES................................................................................................................................186

5.1 INTRODUCTION ................................................................................................... 186

5.2 CASE STUDIES IN TEXAS .................................................................................. 186

5.3 CASE STUDIES IN LOUISIANA ......................................................................... 207

5.4 SUMMARY ............................................................................................................ 287

5.5 REFERENCES ........................................................................................................ 288

CHAPTER 6. FINDINGS, CONCLUSION, DISCUSSION, AND FUTURE WORK........290

6.1 DISCUSSION ......................................................................................................... 294

6.2 STUDY LIMITATIONS ......................................................................................... 296

6.3 FUTURE WORK .................................................................................................... 297

APPENDIX A. INDIVIDUAL EPD COMPILATION.........................................................300

APPENDIX B. INDUSTRY WIDE AVERAGE EPD COMPILATION.............................310

APPENDIX C. SURVEY PERFOMED IN LOUISIANA AND ASSOCIATED

RESULTS..............................................................................................................................315

APPENDIX D. RESULTS OF LOUISIANA SURVEY AND DEVELOPED EPD FOR

LOUISIANA.........................................................................................................................327

APPENDIX E. INVENTORY VALUES FOR TRUCKS USED IN THE

TRANSPORTATION MODULE.........................................................................................342

APPENDIX F. LCCA FOR TEXAS....................................................................................344

VITA.....................................................................................................................................346

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DEFINITIONS

Average data These are average data points across a

number of products, material or process, in

case the data comes from more than one

supplier.

Characterization factor A factor extracted from a characterization

model and used to convert a lifecycle

inventory into a category indicator

Characterization The process where the lifecycle inventory

data are transformed into indicators of

impact to human and ecological health. The

characterization step allows a comparison of

the lifecycle inventory inside each impact

category;

Cradle to gate A part of the lifecycle of a product from the

extraction process (cradle) to the gate (the

point where the material leaves the factory

before inputs as another material into the

manufacturing process.

Declared unit A unit used when the function and the

reference unit in the whole lifecycle of the

product cannot be determined (ISO 21930)

Eco-label An Environmental Declaration or label

providing information about a product or a

service in terms of its environmental

performance or specific environmental

traits. Eco-labels have various forms, such

as statement, symbol, or graphic forms.

Environmental Product Declaration A claim made to represent the

environmental traits of a product or service.

It should be noted that an environmental

label can take various forms, such as a

statement, a symbol, or a graphic (ISO

10420) form.

Equivalent unit Numerous emissions get in the

characterization for the same unit. For

example, 1 g N2O contributes as much to

the global warming as 310 g CO2. Therefore

the 1 g N2O is equal to 310g CO2-

equivalents.

Functional unit The process that defines the service that

needs to be delivered by a product.

Impact category A category representing environmental

issues of a concern. The lifecycle inventory

results can therefore be assigned to these

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environmental categories.

Lifecycle assessment (LCA) The process of evaluating the potential

environmental impact of a product through

its entire lifecycle (ISO 14040).

Lifecycle inventory A part of the lifecycle assessment where the

quantification and compilation of inputs and

outputs for a product throughout the entire

lifecycle occur.

Normalization Expressing the environmental impacts in a

manner which can be compared.

Product category A set of products that can satisfy the same

function (ISO 14025).

Product category rule Specific rules and guidelines to develop

Environmental Declaration Type III for a

product category (ISO 14025).

System boundary Principles specifying the unit processes that

should be included in a product system.

Third party A person, body, or entity that is independent

of the parties involved. In most of the cases,

the parties involved are the supplier and the

purchaser.

Type III Environmental Declaration This is quantified environmental data using

a pre-defined set of categories. Also, there is

additional environmental information that

can be included. The additional set of

information is based on ISO 14040 and ISO

14044.

Upstream process The process of concrete material production

which is outside the concrete facility.

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ABBREVIATIONS AND ACRONYMS

AADT Annual Average Daily Traffic

AASHTO American Association of State Highway and Transportation

Officials

ACEC American Council of Engineering Companies

ADOT Arizona Department of Transportation

AP Acidification Potential

APWA American Public Works Association

ASCE American Society of Civil Engineers

ASTM American Society for Testing and Materials

BCA Benefit Cost Analysis

Caltrans California Department of Transportation

CBW Concrete Batching Water

CDOT Colorado Department of Transportation

CEQ Council on environmental Quality

CExC Net Exergy Consumption

CFC-11 Trichlorofluoromethane

CH4 Methane

Cl Chloride

CO Carbon Monoxide

CO2 Carbon dioxide

CO3 Construction Congestion Cost

CO4 Carbon tetroxide

CRCP Continuously Reinforced Concrete Pavement

CWW Concrete Washing Water

DelDOT Delaware Department of Transportation

DOT Department of Transportation

EC Total Primary Energy Consumption

EconW Economic Weight

EIS Environmental Impact Statements

EnvW Environmental Weight

EOL End Of Life

EP Eutrophication Potential

EPA Environmental Protection agency

EUAC Equivalent Uniform Annual Cost

FHWA Federal Highway Administration

GHG Green House Gases

GWP Global Warming Potential

H2SO4 Sulfuric Acid

HMA Hot Mix Asphalt

HW Hazardous Waste

ICC Internally Cured Concrete

IO-LCA Input Output LCA

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IRI International Roughness Index

ISO International Standards Organization

JPCP Jointed Plain Concrete Pavement

LaDOTD Louisiana Department of Transportation and Development

lb Pounds

LCA Lifecycle Assessment

LEED Leadership in Energy and Environmental Design

LL Layer length

LT Layer thickness

Lw Layer width

LWC Lightweight Aggregate Concrete

m Meter

MDOT Minnesota Department of Transportation

MEPDG Mechanistic Empirical Pavement Design Guide

MJ Mega joules

MOR Modulus of Rupture

N Nitrogen

N2O Nitrous Oxide

NEPA National Environmental Policy Act

NHW Non Hazardous Waste

NIST National Institute of Standards and Technology

NOx Nitrogen Oxide

NPV Net Present Value

NRE Non Renewable Energy

NRMCA The National Ready Mix Concrete Association

NRMR Depletion of Non Renewable Material Resources

NYSDOT New York State Department of Transportation

O3 Ozone

ODOT The Ohio Department of Transportation

ODP Ozone Depletion Potential

Oz Ounces

Pb Lead

PCC Portland Cement Concrete

PCR Product Category Rule

PM10 Particulate Matter (10 micrometers or less in diameter)

PM2.5 Particulate Matter (2.5 micrometers or less in diameter)

POCP Photochemical Ozone Creation Potential

Psi Pound per square inch

RE Renewable Energy

RMR Use of Renewable Material Resources

RPE Use of Renewable Primary Energy

RPLCCA Rigid Pavement Lifecycle Cost Analysis

SAB Science Advisory Board

SCM Supplementary Cementitious Material

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SETAC Society of Environmental Toxicology and Chemistry

SLCA Social Lifecycle Assessment

SMA Stone Mastic Asphalt

SO2 Sulfur Dioxide

STARS Sustainability Tracking, Assessment & Rating System

TxDOT The Texas Department of Transportation

U.S United States

VOC Volatile Organic Compounds

WFL Western Federal Lands

WSDOT Washington Department of Transportation

yd Yard

x

ABSTRACT

One of the most important tools in assessing rigid pavement design sustainability (or

environmental impact) is a lifecycle assessment (LCA), which may be applied in any stage of

a product’s lifecycle from cradle to grave, such as pavements. Although LCA was the focus

of much research and codification by organizations such as the International Organization for

Standards and the Society of Environmental Toxicology and Chemistry, limitations exist,

such as a) LCA is time consuming; and b) the used data may become outdated, inaccurate,

biased, incomplete, and/or expensive to use. These limitations are not a deficiency in LCA as

a tool, but in the manner in which various researchers apply the limitations differently.

The objective of this study is to develop a methodology to assess rigid pavement

sustainability using Environmental Product Declarations (EPDs) as a quantification tool.

EPDs are defined as quantified environmental data for a product, based on a pre-set category

of parameters, defined in the ISO 14040 series of standards (ISO 14025). EPDs were

established to homogenize assumptions while performing an LCA. In fact, EPDs follow the

same LCA procedure for quantifying the environmental impact. However, the method used to

issue an EPD importantly guarantees consistency in the data collection process, thus enabling

a comparison between products by fulfilling the same function as well as limiting the

discrepancies that could exist when different researchers perform an LCA.

To achieve this objective, a new pavement design framework was developed to

incorporate this sustainability evaluation criterion. After the design passes the technical

evaluation, the framework will assess pavement sustainability outside the scope.

The framework will enable alternative design comparison between various products,

as well as product benchmarking that uses EPD as a data source. The scope includes a cradle

to gate analysis (using EPD), as well as the transportation stage from the manufacturer’s

location to project location. The transportation stage from the manufacturer’s location to

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project location was assessed using LCA. Various case studies will be provided to validate

the new framework. The framework was used to assess the total sustainability score of

various alternatives in terms of which one has a higher/ lower score. However, these

differences were insignificant. Results also proved that the transportation stage represents an

important criteria, and the total environmental impact was sensitive to a change in this factor.

1

CHAPTER 1. INTRODUCTION

The United Nations defined sustainability in 1987 as “meeting the needs of the

present without compromising the future generations to meet their own needs.” This

definition gained wide acceptance and was known as the Brundtland Commissions.

Moreover, the sustainability definition was defined as having three pillars: environmental,

economic, and social aspect.

Later, other sustainability definitions emerged; however, most of them included the three

pillars of sustainability, previously defined by Brundtland: the economy, the environment,

and social aspect (Georgia Institute of Technology 2011). The three sustainability pillars are

illustrated in Figure 1.

Figure 1. The three sustainability pillars (Green Art Lab Alliance)

Currently, the United States has no national policy on sustainability (Highfield, 2011).

The U.S. Department of Transportation has not yet fully incorporated environmental impacts

into decision making in applications such as pavement design; more specifically, the

2

Mechanistic Empirical Pavement Design Guide (MEPDG). The MEPDG is considered a

major change for pavement design, and provides a comprehensive method for analyzing new

and rehabilitated pavements. The word “mechanistic” denotes the use of engineering

mechanics, leading to a design that has the following components (Huang et al., 2015):

• The theory to predict pavement critical responses, such as stresses and strains and their

relation to traffic and climatic conditions.

• The relationship between critical pavement response and observed distresses, which is

known as the empirical part.

Moreover, the MEPDG includes calibration procedures for local conditions and measures for

design reliability. The MEPDG may be used to analyze causes for pavement distresses, such

as cracking and faulting in rigid pavement design (FHWA, 2015).

However, despite all these advantages, the MEPDG does not incorporate sustainability

into its design framework. In other words, environmental impacts such as Global Warming

Potential (GWP), Acidification Potential (AP), Eutrophication Potential (EP), and Ozone

Depletion Potential (ODP) are not evaluated for the designs performed; designs are solely

analyzed for technical performance aspects.

One of the tools to assess the first pillar of sustainability (environmental aspect) is

lifecycle assessment (LCA). Lifecycle assessment is a method to evaluate the environmental

impact of a product or a service. LCA may be applied at any stage of the product’s lifecycle

from cradle to grave, such as pavements (Reap et al., 2008). Lifecycle assessment has been

the focus of much research. However, despite its popularity and codification by organizations

such as the International Organization for Standards, together with the Society of

Environmental Toxicology and Chemistry, life assessment still has various drawbacks: Not

only does lifecycle assessment remain time consuming, but the accompanying data also may

3

be outdated and/or inaccurate (University of Michigan, 1995), depending on the data

collection method and year.

Moreover, other problems related to the use of LCA include: comparability issues

when performing similar studies, using either different data sources or different temporal

representations. Such variations may lead to discrepant results. These problems are

summarized in Table 1 (Williams, 2009). It should be clearly stated that these

discrepancies are caused by researchers who apply LCA differently, and not a drawback in

LCA as a tool or method.

Table 1. Problems associated with the use of LCA (Williams 2009)

Category Data source

Data source Some sources may be using

literature, while others may be

using measurements

Technological representation Laboratory vs. plant data

Temporal representation Old vs. new data

Geographical representation One source may be using U.S.

data, while the other may be

using European data

Other tools to evaluate the environmental impact of a product are Environmental

Product Declarations (EPDs). EPDs are defined as quantified environmental data for a

product, based on a pre-set category of parameters, defined in the ISO 14040 series of

standards (ISO 14025). EPDs were established to homogenize assumptions while performing

an LCA (Mukherjee & Dylla, 2017). In fact, EPDs follow the same LCA procedure for

quantifying the environmental impact. However, the method used to issue an EPD

guarantees consistency in the data collection process (Mukherjee & Dylla, 2017), thus

enabling the comparison between products fulfilling the same function (Fet & Skaar, 2006;

Fet et al., 2009) and decreasing any discrepancy that could happen, when different

researchers perform the same LCA study.

4

EPDs are based on a document called Product Category Rule (PCR). In this study, the PCR

used are concrete PCR. PCR provides reporting criteria for EPD content in order to guarantee

its consistency. In other words, PCR were issued to guarantee that EPDs for similar products

are based on the same data (Shepherd, 2015). Specifically, PCR outlines the rules for setting

up an EPD, such as mandatory and optional impact categories that may be included in EPDs

(Carbon Leadership Forum, 2013).

Moreover, the PCR document defines the following criteria to guarantee consistency

in the EPDs produced: a) goal, b) PCR validity, c) declared unit, d) use and comparability, (k)

system boundaries, (l) impact categories, (m) criteria for the exclusion of inputs and outputs,

(n) data selection, (o) data quality and validity, (p) allocation assumptions, and (q) how to

report the content of EPD. Also, the PCR document outlines the system boundary, as well as

the various processes that should be included, such as:

• Raw Materials Supply: This process includes extraction, handling, and processing of the

materials, including fuels used in the production of concrete.

• Transportation: This process includes the transportation of materials from the supplier to

the gate of the concrete producer.

• Manufacturing (core process): This process includes the energy used to store, move,

batch, and mix the concrete, as well as operate the facility.

• Construction Transportation: This process is optional, and includes transportation of

concrete from the producer’s gate to the construction site.

The development process of a PCR can be made by various entities such as industry,

third party, or a manufacturer (Shepherd, 2015). In case of similar products across the

industry, such as concrete, the PCR is developed under the supervision of a technical

association or a trade. To guarantee credibility, various stakeholders input the rules for

consistency in setting up the PCR (Shepherd, 2015). Afterward, independent experts then

5

revise the PCR draft for ISO 14044 compliance, in order to guarantee that the LCA data used

offers characterization for the environmental impacts of the products used (Shepherd, 2015).

The process of issuing an EPD requires verification to guarantee its accuracy and to

ascertain that the EPD is unbiased. This verification process is performed by various

stakeholders, as well as a third party verifier (Mukherjee & Dylla, 2017). The third party

verifier validates the EPD and makes certain as well that the EPD adheres to the PCR

(Mukherjee & Dylla, 2017). After the verification process and after addressing all the

comments of stakeholders, the EPD is finally published (Shepherd, 2015).

To assess the second pillar of sustainability (the economic aspect), a lifecycle cost

analysis (LCCA) is performed. Pavement LCCA was first discussed in the Red Book in 1960

by the American Association of State Highway and Transportation officials (AASHTO)

(Wilde et al., 2001). In early 1990, pavement LCCA was included in the federal literature by

using several vehicle-operating cost models (Zaniewski et al., 1982; Watanatada et al., 1987;

Paterson & Attoh-Okine, 1992; Uddin, 1993). In 1995, FHWA made LCCA a requirement

for National Highway System projects costing more than $25 million. However, this policy

was annulled in 1998, by the Transportation Equity Act. Nevertheless, FHWA and AASTHO

are still providing guidance for states for developing an LCCA procedure for each state.

1.1 PROBLEM STATEMENT AND RESEARCH QUESTIONS

Based on the previous research for assessing the environmental impact of pavements, a

new tool is highly needed to evaluate the sustainability of rigid pavement design. This tool

should overcome the current shortcomings of sustainability, mostly related to comparability.

The developed tool will be used to answer the following questions:

• What is the impact of the transportation stage on the overall environmental impact per

alternative? (based on the scope of this study)

• What is the impact of (raw material extraction and manufacturing) on the overall

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environmental impact per alternative? (based on the scope of this study)

1.2 GOAL AND OBJECTIVES

In response to these questions, the goal of this study is to improve the design

sustainability of rigid pavements. The objective of this study is to develop a decision making

tool to evaluate rigid pavement design sustainability (focusing on environmental and

economic aspects, as the social aspect models are still undeveloped), using Environmental

Product Declarations previously described, as well as cost data for the State of Louisiana. The

use of EPD should therefore resolve existing problems associated with comparability issues.

Moreover, the use of EPD should add more credibility and consistency to the data

used, since these data were previously verified. Therefore, the objectives of this study are 1)

to alter the existing pavement design framework to include the new sustainability criteria; 2)

to design an Environmental Product Declaration database (an EPD scope, covering a cradle to

gate analysis); and 3) to design a cost analysis database. Moreover, it should be noted that the

scope of the study will include the transportation impact from manufacturing to project

location, as illustrated in Figure 2.

Therefore, to cover this stage, the objectives would continue as: 4) a transportation

impact analysis to be performed for various truck types and fuel types; 5) a software to be

developed to include the databases (the software was fully developed by Qiandong Nie, a

programmer, and based on the framework developed in this study), as well as facilitate data

incorporation into the new framework; and 6) case studies to be performed to test and

validate the new framework.

Figure 2. The scope of the study

The scope of the study is highlighted; the arrows represent product transportation.

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1.3 RESEARCH APPROACH AND IMPLEMENTATION

To accomplish the aforementioned objectives, this study will perform the following

tasks:

1) remodeling the current pavement design framework, 2) designing the EPD database, 3)

designing the cost analysis database, 4) performing the transportation impact analysis, 5)

modifying and incorporating the data into the framework, and 6) assessing the new

framework.

The first task is to remodel the existing pavement design framework to include the

new sustainability criteria. This will be accomplished through evaluating both the

environmental and economic impacts of the design. The design will no longer be based solely

on the technical performance, but will also evaluate the environmental and economic criteria.

This process is documented in Chapter 3.

The second task is to design an EPD database. This will be performed through an

extensive EPD collection process on a Louisiana level, as well as on a national level. This

database will be available online, free of charge for anyone to use; therefore, EPDs for other

states will be provided. The EPD data collection process was performed through extensive

communication with the industry, an internet web search, and by requesting product data

sheets, including mix design breakdowns. This is documented in Chapter 3.

The third task is to design a cost analysis database to perform lifecycle cost analysis

for the State of Louisiana. This was performed through an extensive data collection process

from the Louisiana Department of Transportation and Development database. The database

was divided into two sections: initial cost items (costs occurring at the present) and future

cost items (cost for the maintenance and rehabilitation items). The first section contains an

initial material cost for the mix design collected from the manufacturer. The second section

contains material prices, labor, equipment, and overheads collected from the Louisiana

8

Department of Transportation and Development database. The future cost includes

maintenance and rehabilitation activities that may occur to concrete pavement during its

lifecycle. These initial and maintenance and rehabilitation costs are used to perform a

lifecycle cost analysis. This process is documented in Chapter 3. Tasks 1, 2, and 3, previously

discussed, are summarized in Figure 3.

Moreover, to account for the environmental impact of transportation from the

manufacturer to the project location, lifecycle assessment will be performed for various types

of trucks and fuels. Trucks were divided by weight into three categories: light duty truck,

medium duty truck, and heavy duty truck. Two types of fuels were evaluated: diesel and

gasoline. This process is documented in Chapter 3.

Figure 3. Work tasks and expected outcomes (Tasks 1, 2 and 3)

To illustrate the process of incorporating the new sustainability criteria into the new

pavement design framework, various data modifications were performed to make certain

these remain consistent. For example, while the environmental data drew inventory data from

the transportation module, the environmental impacts data drew data coming from the EPDs.

These data consisted of different units. Moreover, the cost analysis data displayed initial cost

9

data occurring at the present, while maintenance and rehabilitation costs showed data to occur

in the future. Some modifications were performed to assure that the data were evaluated at

the same point in time. This procedure is described in the implementation chapter in Chapter

4. As a result, the output of this Chapter should be a complete framework, ready and in place

to implement and apply in case studies.

To facilitate the manipulation of the data and their integration into the new rigid

pavement design framework, software was developed to store and query data from EPD, cost

analysis, and transportation impact. Full design credit for software development goes to the

programmer Qiandong Nie, who developed the software based on the framework presented in

this study. The software has a simple user interface, requires no programming background,

and remains expandable to enable future data expansion. This process is described in Chapter

4. Tasks 4, 5, and 6, previously described, are illustrated in Figure 4.

Finally, case studies will be performed to assess the new framework. Case studies will

include various states, such as Texas and Louisiana. These case studies are performed in

Chapter 5. Chapter 6 will present the conclusion, recommendations, and future work to be

performed later. To facilitate the navigation process, the tasks are also illustrated per chapter

number in Figure 5. It should be noted that the literature review was not thoroughly described

as a task, since this is a part performed in any study.

10

Figure 4. Work tasks and expected outcomes (Tasks 4, 5, and 6)

Figure 5. Various chapters and tasks

11

1.4 CONTRIBUTION TO THE BODY OF KNOWLEDGE

This study develops an innovative methodology for rigid pavement design by

introducing a new framework and a ready for implementation tool to quantify the

sustainability of rigid pavement design from cradle to gate, using data from EPD. The data

are based on a pre-defined set of categories and based on the same system boundary which, in

turn, should solve the comparability issue associated with other sustainability tools, such as

lifecycle assessment. Moreover, the use of EPD should add more credibility to the results,

since EPD are verified data. The new framework assesses designs based on economic and

environmental criteria. The new framework should enable the comparison of various

alternatives as well.

1.5 REFERENCES

Brown, E., Kelly, B., Dougherty, M., & Ajise, K. (2015). Caltrans strategic management

plan. Retrieved from

http://www.dot.ca.gov/perf/library/pdf/Caltrans_Strategic_Mgmt_Plan_033015.pdf

Carbon Leadership Forum. Product Category Rules (PCR) for ISO 14025 Type III

Environmental Product Declarations (EPDs). University of Washington. Retrieved

from http://swarmdev2.be.washington.edu/2017/01/03/concrete-pcr/

Fet, AM and C Skaar. "Eco-Labeling, Product Category Rules and Certification Procedures

Based on ISO 14025 Requirements." International Journal of Life Cycle Assessment,

vol. 11, no. 1, n.d., pp. 49-54. EBSCOhost,

libezp.lib.lsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=e

dswsc&AN=000234658600008&site=eds-live&scope=site&profile=eds-main.

FHWA. (2014, October). Pavement sustainability. Retrieved September, 2016, from

https://www.fhwa.dot.gov/pavement/sustainability/hif14012

FHWA. (2015). Mechanistic – Empirical Pavement Design. Retrieved from

https://www.fhwa.dot.gov/resourcecenter/teams/pavement/pave_3PDG.pdf

Georgia Institute of Technology. (2011). Transportation planning for sustainability

guidebook. Retrieved December, 2016, from

http://onlinepubs.trb.org/onlinepubs/archive/mepdg/part_12_cover_ack_toc.pdf

Highfield, C. (2011). Developing a methodology for integrating environmental Impact into

the decision making process. Retrieved October 17, 2016, from Virginia Polytechnic

Institute and State University from https://theses.lib.vt.edu/theses/available/etd-

05112011-150800/unrestricted/Highfield_CL_T_2011.pdf

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Huang, Baoshan, et al. (2005). "64.2.1 Design Input for MEPDG Software." Paving Materials

and Pavement Analysis - Proceedings of Sessions of Geoshanghai 2010, June 3–5,

2010 Shanghai, China, American Society of Civil Engineers (ASCE), 2015.

EBSCOhost,

libezp.lib.lsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=e

dsknv&AN=edsknv.kt00UA82OT&site=eds-live&scope=site&profile=eds-main.

Lent, T. (2003). Toxic Data Bias and the Challenges of Using LCA in the Design

Community. Retrieved February 7, 2017, from

http://www.usgbc.org/Docs/LEED_tsac/Toxic_Data_Bias_LCA_paper-Lent.pdf

Mukherjee, A and H Dylla (2017). Lessons learned in developing an Environmental Product

Declaration program for the asphalt industry in North Ameri. Retrieved (2017)

Ramani;, T., Potter;, J., DeFlorio;, J., Zietsman, J., & Reeder, V. (2011). A Guidebook for

Sustainability Performance Measurement for Transportation Agencies. Retrieved

from https://www.nap.edu/download/14598#

Reap, J, et al. "A Survey of Unresolved Problems in Life Cycle Assessment - Part 1: Goal

and Scope and Inventory Analysis." International Journal of Life Cycle Assessment,

vol. 13, no. 4, n.d., pp. 290-300. EBSCOhost,

libezp.lib.lsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=e

dswsc&AN=000256765300003&site=eds-live&scope=site&profile=eds-main.

Shepherd, D. (2015). Environmental Product Declarations - Transparency Reporting for

Sustainability. IEEE-IAS/PCA Cement Industry Technical Conference, Cement

Industry Technical Conference, 2016 IEEE-IAS/PCA,p. 1. EBSCOhost,

doi:10.1109/CITCON.2016.7742664.

University of Michigan (1995). Note on Lifecycle Analysis. Retrieved December 7, 2016,

from http://www.umich.edu/~nppcpub/resources/compendia/CORPpdfs/CORPlca.pdf

Williams, A. (2009). Life Cycle Analysis: A Step by Step Approach. Retrieved from

http://www.istc.illinois.edu/info/library_docs/tr/tr40.pdf

Zietsman, J., & Ramani, T. (2011). Sustainability Performance Measures for State Dots and

Other Transportation Agencies. Retrieved from

http://onlinepubs.trb.org/onlinepubs/nchrp/docs/NCHRP08-74_FR.pdf

13

CHAPTER 2. LITERATURE REVIEW

2.1 INTRODUCTION

This chapter will present existing tools for assessing pavement sustainability. The

environmental, social, and economic impacts will be presented as the three pillars of

sustainability.

The chapter will explain the tools necessary to assess the environmental impact, such

as lifecycle assessment and its various stages, followed by an explanation of problems

associated with lifecycle assessment or more specifically, problems associated with pavement

lifecycle assessment. This presentation will be accomplished through studying various

pavement lifecycle assessment case studies from cradle to grave, in order to highlight all

possible issues that may arise while performing a lifecycle assessment, thereby identifying

current gaps for future work. Then the chapter will present other tools to assess the

environmental impact, such as rating tools, environmental assessment, and environmental

impact statements.

Afterward, the chapter will assess another sustainability pillar, the social impact,

which will be followed by the economic impact. The economic impact will present concepts

such as initial cost vs. maintenance and rehabilitation cost, as well as time value of money

and associated equations.

Finally, the current pavement design framework is illustrated and explained at the end

of the chapter. The framework does not incorporate any of the sustainability criteria

previously illustrated. This framework will be modified in later chapters to incorporate

sustainability criteria.

14

2.2 LIFECYCLE ASSESSMENT (LCA)

Lifecycle assessment dates to the 1960s. The reason for performing LCA emanates from a

concern about limitations in raw materials and energy resources, as well as the need to predict

future supplies. One of the first studies performed was by Harold Smith, who calculated a

cumulative energy requirement to produce chemical intermediates at the World Energy

Conference in 1963 (Curran, 2006).

In 1969, researchers performed an internal LCA for the Coca Cola Company. This

study opened the door for current methods of lifecycle inventory analysis in the United

States. The objective of this study was to compare different beverage containers to evaluate

which container not only had the lowest environmental impact, but also consumed less

material. The scope of this study included the quantification of those raw materials and fuels

which were used. In the 1970’s, other companies in the United States, as well as Europe, used

LCA for various purposes (Curran, 2006).

From 1975 to the early 1980s, the environmental concerns shifted to hazardous waste.

However, at this point in time, inventory analyses were used, and the studies performed

focused on energy issues. In 1998, solid waste became a worldwide issue, leading LCA users

to expand LCA to include the assessment of solid waste (SETAC 1991; SETAC 1993;

SETAC 1997).

Lifecycle assessment evaluates the environmental impact of a product, together with

its complex systems of products and processes. LCA examines all inputs and outputs over the

lifecycle of a product, starting from the production of raw materials to the lifecycle end. In

addition, LCA considers the transportation between the various stages. Lifecycle assessment

analysis originally analyzed emissions to air, land, and water. Later, LCA expanded to

include energy, resource use, and chemical emissions.

15

Initially, the focus was on products and packaging, and then the focus moved to

infrastructure (Hunt & Franklin, 1996). In the years 1990 to 2000, this LCA method was

standardized by the International Organization for Standardization (ISO) (SAIC, 2006). As

illustrated in Figure 6, the lifecycle assessment consists of four phases: a) goal and scope

definition; b) lifecycle inventory assessment; c) impact assessment, and d) lifecycle

interpretation. These phases are explained in the coming section.

Goal and scope definition

Interp

retation

Lifecycle inventory

assessment

Impact assessment

Figure 6. Lifecycle assessment framework (Kendall 2012)

2.2.1 GOAL AND SCOPE DEFINITION PHASE

The goal and scope phase defines the goal and the purpose for conducting a lifecycle

assessment for a certain product (EPA, 2006). Definition of the goal, coupled with the scope

of the study is the step that will define the amount of time and resources needed in the study

from beginning to end. The following points should be considered before setting a goal for

the study: 1) determining the goal of the project, 2) determining the level of specificity, and

3) determining what type of information is needed for decision makers (EPA, 2006).

2.2.2 LIFECYCLE INVENTORY PHASE

The lifecycle inventory is the LCA phase where the data collection occurs. The

process details a tracking of the flows coming in and out of the system, inclusive of raw

material, resources, energy, and water by a specific substance. Figure 7 illustrates the

lifecycle inventory phase (Athena, 2017). As illustrated, the system is indicated at the middle

of the picture with inputs as well as outputs coming in and out of the system (Athena, 2017).

16

In this figure, or in this study, the resulting output includes emissions and waste. The output

varies, depending on the study.

2.2.3 LIFECYCLE IMPACT ASSESSMENT PHASE

Lifecycle impact assessment is a process whereby the magnitude and significance of

potential environmental impacts, as well as human health impacts, are identified. The

identification involves a product or a service used during the lifecycle inventory stage.

Figure 8 illustrates the relationships between a lifecycle inventory midpoint and relevant

endpoint impacts that require protection. For example, there are elementary flows causing

Global Warming Potential (GWP), which impact human health and the natural environment.

Other elementary flows might only impact resource depletion at the midpoint, and/or natural

resources at the end.

Moreover, the lifecycle impact assessment phase is composed of many sub-phases such

as: a) selection and definition of impact categories, b) classification, c) characterization, d)

normalization, e) weighting, f) evaluating and reporting LCIA results, and g) interpretation

(EPA, 2006). As defined by ISO 14042, the following steps are mandatory in performing a

Material

s

Raw material extraction

Transportation

Manufacturing

Transportation

Construction

Use

End of life

Energy

Water

Emission

s

Waste

Figure 7. Lifecycle Inventory stage (Athena 2017)

17

lifecycle assessment: definition of impact category, classification, and categorization; the

other steps are optional. These sub-phases will be explained in detail below.

Figure 8. Lifecycle inventory, midpoint and end of area protection (European

platform for lifecycle assessment 2017)

2.2.4 SELECTION AND DEFINITION OF IMPACT CATEGORIES

The first step in performing a lifecycle impact assessment is the selection of those

impact categories which will be included in both the goal and scope definition. This process

should guide the data collection process of the lifecycle inventory. The items included in the

lifecycle inventory have both an environmental impact, as well as a health impact. As an

Human

health

End area of protection

Natural

environment

Natural

resources

Lifecycle

inventory Midpoint

18

example, an environmental release in the lifecycle inventory phase may have an impact on

human health, such as causing cancer, as well as an impact on the environment, such as

causing acid rain (EPA, 2006).

2.2.4.1 Classification

The objective of the classification step is to consolidate lifecycle inventory into impact

categories (example, GWP, etc…). The process becomes easy for the lifecycle inventory

contributing to only one impact category. As an example, Carbon Dioxide only contributes to

the Global Warming Potential (EPA, 2006). However, for a lifecycle inventory contributing

to more than one impact category, there are various ways to divide this inventory among

other impact categories, such as (ISO, 1998),

• Distributing a portion of the lifecycle inventory to the other impact categories these cause.

This occurs when results are dependent.

• Conveying all lifecycle inventory to the various impact categories involved. This occurs

when results are independent.

2.2.4.2 Characterization

The impact characterization stage is the process where the lifecycle inventory data are

transformed into indicators of impact to human and ecological health (EPA, 2006). The

characterization step allows a comparison of the lifecycle inventory inside each impact

category; as a result, characterization transforms different inventories to impact indicators

that may be compared in a more direct fashion. The equation for characterization is illustrated

in Equation 1.

(1)

As an example, both Chloroform and Methane contribute to GWP. The characterization

factor for Chloroform is 9 and for Methane, the characterization factor is 21. Therefore, a

quantity of 20 lb Chloroform contributes to a total of: 20 lb × 9 = 180 towards Global

19

Warming Potential, while a quantity of 10 lb Methane contributes to 10 lb × 21 = 210

towards Global Warming Potential.

Importantly, the process of selecting a characterization value is controversial and varies

from one impact to the other. There is some consensus on characterization values, such as the

value of GWP (EPA, 2006). However, for impacts such as resource depletion, there is no

consensus as yet on the characterization value (EPA, 2006). Therefore, any assumptions for

the characterization value should be well documented.

As a convention used in this study, Table 2 illustrates the final units that will be used for

each environmental impact. For example, there are various lifecycle inventories leading to

Global Warming Potential, such as Carbon Dioxide, Nitrogen Dioxide, Methane, etc.

Therefore, all these inventories will be converted into units of Carbon Dioxide equivalent.

The same concept applies to other environmental impacts

Table 2. Convention used in this study

Name End point impact Examples of LCI

data

Description of

characterization factor

Global Warming

Potential (GWP)

Soil moisture loss,

forest loss, longer

seasons.

Carbon Dioxide

(CO2), Nitrogen

Dioxide

(NO2),Methane

(CH4)

Converts LCI data to

(CO2) equivalents

Ozone Depletion

Potential (ODP)

Greater ultraviolet

radiation

Chlorofluorocarbons

(CFCs), Halons

Converts LCI data to

trichlorofluoromethane

(CFC-11) equivalents.

Eutrophication

Potential (EP)

Phosphorus and

Nitrogen enter

water bodies

causing excessive

plants growth

Phosphate (PO4),

Nitrogen Oxide

(NO)

Converts LCI data to

Nitrogen equivalent

Acidification

Potential (AP)

Water body

acidification,

corrosion for

buildings

Sulfur Oxides

(SOx),Nitrogen

Oxides (NOx),

Hydrochloric Acid

(HCL)

Converts LCI data to

Sulfur Dioxide SO2

equivalent

Photochemical

Ozone Creation

Potential (POCP)

Decreased

visibility, eye &

lung irritation

Non-methane

hydrocarbon

(NMHC), Ozone

Converts LCI data to

Ozone O3 equivalent

20

2.2.4.3 Normalization

Normalization is used to express the impact indicators in a manner that can be

compared among impact categories (EPA, 2006). This process occurs by dividing the

indicators by a selected reference value. The equation used for normalization is illustrated in

Equation 2.

(2)

For example, by analyzing values in EPD for a random mix design (1yd3), the GWP = 346 kg

CO2 eq and the Ozone Depletion Potential (ODP) = 3.99E-06 kg CFC-11 eq, which means

these values are not on the same scale or units. However, by normalizing these values, the

new values then become (Stranddorf et al., 2005) the following:

Normalized value for GWP = (346 kg CO2 eq)/ (24000 kg CO2 eq) = 0.0144

Normalized value for ODP = (3.99E-06 kg CFC-11 eq )/(0.16 kg CFC-11 eq) = 2.49 × 10-5

According to EPA (2006), there are various reference values that may be used, such as

• The total emissions or resource use for a given area. These emissions can be either global,

regional, or local.

• The total emissions or resource use given for a certain area per capita

• The ratio from one alternative to the other

• The highest value amongst all alternatives

The reference value that will be selected in this study is the total emissions given per capita.

2.2.4.4 Grouping

Grouping is the process of classifying impact categories into sets to ease the

interpretation of the results. Normally, the grouping process tends to sort or rank indicators.

Grouping is performed in one of the following ways:

• Indicators are sorted by characteristics, such as emissions (to water, air) or location

(regional, global, etc.)

21

• Indicators are sorted by classifying these into categories of low, medium, high, etc.

2.2.4.5 Weighting

The weighting process for LCA is the process of assigning weights to various impact

categories, based on the importance (EPA, 2006). This weighting procedure importantly

reflects a stakeholder preference. The weighting procedure could differ, depending on

stakeholders’ opinions; therefore, the reason for assigning any weight should be documented

(EPA, 2006). For example, harmful air emissions are of higher concern in areas with an air

attainment zone than in areas with improved air quality; therefore, impacts related to air

should be assigned higher weights in air attainment zones (EPA, 2006). According to EPA

(2006), the weighting procedure should follow the following rules:

• Identifying the importance of the various impacts to stakeholder;

• Determining the weights to be used for the impacts;

• Applying the weights to the impacts.

The equation used for the weighting step is illustrated in Equation 3:

(3)

Where:

• The assigned weights are selected by the stakeholder.

• The calculation procedure for the normalization was previously illustrated in Equation 2.

There are various scenarios that occur when assigning weighting. The first is

subjectivity: The weighting values will change either from one place to another, or by time.

For example, someone located in California may place a higher weight for photochemical

smog than someone in Wyoming (EPA, 2006). Therefore, the selection process of the

weighting criteria should be well documented and explained.

22

Another example illustrating the process of assigning weights is the weights assigned

by the EPA’s Science Advisory Board (SAB) and the Building for Environmental and

Economic Sustainability (BEES) models:

In 1990 and again in 2000, the EPA’s Science Advisory Board (SAB) developed a list of

various important environmental impacts in order to help the EPA allocate its resources. The

EPA used the following criteria to develop the lists: (Lippiatt, 2007). At the end, the EPA

came up with the weights illustrated in Table 3 for various impacts.

• The spatial scale of the impact

• The severity of the hazard

• The degree of exposure

• The penalty of being wrong

Table 3. EPA’s Science Advisory Board weighting criteria (EPA 2000)

Impact category Relative importance

(weight) in %

Global Warming 16

Acidification 5

Eutrophication 5

Fossil Fuel Depletion 5

Indoor Air Quality 11

Habitat Alteration 16

Water Intake 3

Criteria Air Pollutants 6

Smog 6

Ecological Toxicity 11

Ozone Depletion 5

Human Health 11

Later, the BEES performed many calculations and modifications to translate these

SAB results into weights for interpreting LCA. For developing these weights, the National

Institute of Standards and Technology (NIST) gathered volunteering stakeholders in

Maryland on May 2006. Voting interests were grouped into three categories: The first

category was inclusive of the producers (building product manufactures), users (green

23

building designers), and LCA experts. Nineteen different people participated in the panel:

seven producers, seven users, and five LCA experts. Gathered from ASTM International,

these voting interests developed voluntary standards for balancing final results (Lippiatt,

2007). These final results are illustrated in Table 4.

Table 4. BEES stakeholder panel judgement (Lippiatt 2007)

Impact category Relative importance

(weight) in %

Global Warming 29

Acidification 3

Eutrophication 6

Fossil Fuel Depletion 10

Indoor Air Quality 3

Habitat Alteration 6

Water Intake 8

Criteria Air Pollutants 9

Smog 4

Ecological Toxicity 7

Ozone Depletion 2

Human health

(Cancerous Effects)

8

Human health

(Noncancerous Effects)

5

2.2.4.6 Evaluating and reporting Lifecycle Impact Assessment (LCIA) results

After performing all the previous calculations, the results accuracy must be explained.

The accuracy should be well presented by using the goal and scope definition assigned for the

LCA study. When the LCA study is documented, all the assumptions and methodology used

should be clearly stated. When performing LCIA (EPA, 2006), there are various

drawbacks/limitations associated with the use of LCIA, such as:

• The use of LCA does not provide a temporal scale; for example, a five ton discharge of

particulate matter is more dangerous than the same amount released over the entire year.

• Broad inventory: Vague terms are used, such as metals, “VOC” etc…; these words do

not provide accurate information toward assessing the environmental impact.

24

• For example, a ten ton release of a contamination does not mean it is ten times worse

than one ton of contamination (EPA, 2006).

2.2.5 INTERPRETATION PHASE

A lifecycle interpretation phase presents a process whereby the results of the lifecycle

inventory or lifecycle impact assessment are evaluated. After data evaluation, the impacts are

then communicated to decision makers (EPA, 2006). The ISO defined the following two

objectives for the lifecycle interpretation phase: 1) to analyze results, by explaining

limitations and future recommendations; and 2) to present the final LCA result in a manner

that does not contradict the goal of the study (EPA, 2006).

2.2.6 TYPES OF LCA

There are various types of LCA, depending on the goal and scope definition of a

pavement LCA study. These types will be explained as follows:

• Input-Output LCA: The IO-LCA is a top-down method that embraces the full supply

chain of a product in various environmental sectors. The IO-LCA examines all sectors of

the economy by analyzing the flow of goods and services among different sectors

responsible for producing a unit of output from a specified sector (Carnegie Mellon

University).

• Process-Based LCA: Process-based LCA is an environmental analysis method that

computes the inputs and outputs of every process identified within the system boundary

for a given product or service. Each environmental emission related to an individual

process is evaluated. Therefore, the process of LCA necessitates that the system

boundary is well defined. Process LCA is the most detailed and time consuming analysis

that can be performed for a product (Inyim et al., 2016).

25

• Hybrid LCA: Hybrid LCA is a mix of input-output and process methods. This involves

using both economic and environmental data related to a specific process (Inyim et al.,

2016).

• Attributional LCA: The attributional LCA is performed to describe the environmental

physical flows both to and from the lifecycle system; additionally, attributional LCA

uses average environmental data (Attributional and Consequential LCA, 2016).

• Dynamic LCA: Dynamic LCA is defined as an “... approach to LCA, which explicitly

incorporates dynamic process modeling in the context of temporal and spatial variations

in the surrounding industrial and environmental systems.” (Dynamic LCA, Framework

and Application, 2013).

• Consequential LCA: In this type of LCA, the system boundary is performed to

guarantee that the activities included in the analysis reflect the change occurring as a

consequence of a change in decision making (Attributional and Consequential LCA,

2016).

2.3 PAVEMENT LIFECYCLE PHASES

As previously discussed, LCA can be performed to evaluate the environmental impact

of a product or a service during any stage of the product lifecycle, such as pavement.

Pavement lifecycle stages are: materials production, design phase, construction phase, use

phase, maintenance and rehabilitation phase, and end-of-life phase. These phases are

illustrated in Figure 9.

This section is going to thoroughly explain current problems associated with LCA.

Literature reviews pertaining to pavement LCA from cradle to grave were thoroughly read to

identify current gaps for future work.

26

Figure 9. Pavement lifecycle phases (cradle to grave) (Pavement Sustainability 2014)

2.3.1 MATERIALS PRODUCTION

The material production phase includes all activities involved in pavement material

acquisitions, such as mining, crude oil extraction, and processing (refining, mixing, and

manufacturing) as used (Pavement Sustainability, 2014). In addition, plant processes required

to produce concrete, asphalt, mixed aggregates, cement, and additives are included. The

material production phase affects air, water, non-renewable resources, human health, the

ecosystem, and the lifecycle cost (Pavement Sustainability, 2014).

Various studies were performed to compare the material extraction phases for asphalt

and concrete pavement. For example, Horvath and Hendrickson (1998) compared asphalt

pavement with steel-reinforced concrete pavements. The study concluded that asphalt

pavement consumes 40% more energy than concrete pavement for the material extraction

phase. Moreover, the asphalt alternative proved to have lower toxic emissions. The author

clearly stated that there is uncertainty in the data, which may be considered one of the

limitations of this study.

27

Other studies discussed the inclusion/exclusion of the feedstock energy of bitumen

and its subsequent impact in the material extraction phase (Sanetero et al., 2011). As per the

ISO 14044 standards, the feedstock energy in bitumen is defined as “… the heat of

combustion of a raw material input that is not used as energy source to a product system,

measured in higher heating value or lower heating value” (ISO, 14044). There is an extensive

amount of energy stored in bitumen (Sanetero et al., 2011), making a significant issue of the

inclusion or exclusion of such energy in LCA.

Feedstock energy was included in various pavement LCAs, such as the work

performed by Häkkinen and Mäkelä (1996), Nisbet (2001), Athena (2006), and Chan (2007).

The study performed by Häkkinen and Mäkelä (1996) estimated that asphalt pavement

consumes a higher, non-renewable energy (almost twice), compared to a concrete pavement

alternative, when feedstock energy is included. In cases where the feedstock energy is

excluded, the results remained almost similar for both alternatives (Häkkinen & Mäkelä,

1996). This finding confirms the fact that LCA results can be highly affected by the

inclusion/exclusion of feedstock energy.

Another study performed by Nisbet (2001) compared air emissions and energy during

the material extraction phase for asphalt and concrete pavement used in urban collectors and

highway routes. The study was commissioned by the Portland Cement Association (PCA).

The concrete pavement is a JPCP design for both urban collectors and highway routes. The

study presents the data in a very clear format, including the reference for each source. Results

of this study proved that concrete pavement requires less material for both cases, urban

collectors as well as highway routes. In addition, the concrete pavement alternative proved to

have lower air emissions and lower energy, compared to asphalt. The study also performed a

sensitivity analysis on feedstock energy for the asphalt alternative. Results proved that the

feedstock energy in bitumen was significant (Nisbet, 2001).

28

In addition, in 2006 the Athena Institute performed a lifecycle assessment to compare

concrete vs. asphalt pavement. The objective of this study was to compare energy and Global

Warming Potential for concrete vs. asphalt for the materials production phase. The concrete

pavement includes JPCP design. The pavement design was performed using the Mechanistic

Empirical Pavement Design Guide (MEPDG). The feedstock energy of bitumen is included

in the analysis and accounted for with a significant amount of energy per unit of asphalt.

Results of the analysis proved that in the event the feedstock energy is included, asphalt

proves to have a higher energy consumption (from 2 to 5 times) than concrete pavement.

When the feedstock energy is excluded, asphalt still consumes more energy (0.3 to 0.7 times)

than concrete. From all the previous case studies, the inclusion/exclusion of feedstock energy

is a significant matter that should be considered in the analysis, as the final results are highly

altered.

2.3.2 USE PHASE

The use phase includes all activities occurring while the pavement is in operation,

such as rolling resistance, tire pavement noise, lighting, and leaching.

The use phase also includes the interaction that happens between vehicle operation and the

environment. Research proves a relationship between pavement type (pavement structure,

surface roughness) and condition and fuel consumption. One of the factors affecting fuel

consumption is rolling resistance, defined as the process in which pavements affect fuel

consumption (Taylor Consulting, 2002). The following factors affect rolling resistance

(Taylor Consulting, 2002): pavement structure, vehicle mass, pavement temperature, road

roughness, road grade, and vehicle speed. This section will thoroughly present each factor.

2.3.2.1 Pavement structure

The impact of pavement structure may be seen in vehicle fuel consumed while

vehicles travel on pavement. The principle that relates pavement structure to fuel

29

consumption is viscoelasticity, in regard to asphalt pavement (Beuving et al., 2004). This

theory is based on the assumption that flexible pavement deflects under the effect of passing

vehicles. This deflection absorbs the energy that would have been otherwise used to

accelerate the vehicle (Zaniewski, 1989).

Based on this concept, other literature review proves that concrete rigidity prevents

this deflection from happening, and therefore vehicles rolling on concrete pavement consume

less fuel (Sanetero et al., 2011). Various studies were performed to evaluate the impact of

pavement structure/surface on fuel consumption, and specifically, to compare concrete to

asphalt pavement. Some of these studies include the work performed by Zaniewski (1989),

Taylor and Patten (2006), and Taylor and Patten (2002).

Zaniewski (1989) performed a study to assess the impact of pavement surface type on

fuel consumption. The author tried various vehicle types on pavements such as Asphalt

Concrete, Portland Cement Concrete, and Asphalt Concrete surface treatments. The

minimum speed used in the study was 10 miles per hour and the maximum speed was 70

miles per hour. However, few details were provided about the overall pavement design; also,

the study did not consider all pavement conditions, only evaluating pavements in good

condition, which could be considered a limitation of the study. The author concluded that

concrete pavement provided better fuel consumption for trucks than asphalt, by 1%

(Zaniewski, 1989).

Taylor et al. (2006) performed a study to evaluate the impact of pavement structure on

fuel consumption. This study was performed in Ontario, Quebec. The report was initially

prepared for the Center for Surface Transportation Technology. The pavement types included

in the analysis were concrete, asphalt, and composite pavements. The speeds included in the

analysis were 60 kh/hour and 100 km/hour. The study was performed in various times of the

year, and included the seasons of winter, spring, summer (hot and cool) and fall. This study

30

included only pavements in good condition (smooth); therefore, rougher pavements were

excluded.

The author came up with the conclusion that there is little difference between concrete

and asphalt in terms of vehicle fuel consumption. At the end of the report, the author

recommends the following points for inclusion in future work: a) focusing more on the

International Roughness Index, to better estimate the impact that road surface roughness can

have on fuel consumption; b) focusing on analyzing pavement with vehicle speeds of less

than 60 km/hour; and c) expanding the work scope to study other differences between

concrete and asphalt pavement, such as noise absorption and cost of installation (Taylor et al.,

2006)

Further analysis into the studies performed by Zaniewski (1989), Taylor and Patten

(2006), and Taylor and Patten (2002) should be considered; these studies were sponsored by

either the concrete or asphalt industries, and therefore the results might be biased.

Moreover, these studies used various types of vehicles, ranging from light duty to

heavy duty vehicles, in order to test the impact of pavement structure on vehicle fuel

consumption. Further, these studies used various speeds to test the impact of fuel

consumption, with speeds ranging from 30 km/h to 100 km/h. This inconsistency in

performing the experiment could lead to a discrepancy in final results and difficulty in

comparison across other studies. The inconsistency in performances suggests further analysis.

Also, these studies considered the fuel economy improvement over diverse pavement

surface types, such as concrete over asphalt pavement, as well as concrete over composite

pavement; however, the findings did not evaluate all other possible pavement types, which

can be considered a limitation of the study.

31

The tests performed on composite pavement include the works of Taylor and Patten.

The author demonstrated that PCC and composite pavement decreases the amount of fuel

consumed, compared to other pavement types such as HMA (Taylor & Patten, 2002).

The study was originally performed for the National Research Council of Canada’s Center

for Surface Transportation. The research objective evaluated how pavement characteristics

such as pavement structure, pavement roughness, vehicular speed, and configuration, affect

vehicle fuel consumption. The author used heavy duty trucks in his experiment; the pavement

types included concrete pavements, asphalt pavement, and composite pavements. Although

this study included composite pavement, the overall pavement design was not characterized.

2.3.2.2 Pavement roughness

Pavement roughness is a measure for irregularities occurring at road surface

(Pavement Interactive, 2012). These irregularities range from aggregate texture to road

unevenness. In turn, pavement roughness, affects rolling vehicles, by means of vehicle

suspension. Moreover, due to pavement roughness, energy in the form of inertia is lost, due

to the mechanical work and heat created in vehicles; as a result, findings show a higher fuel

consumption (Louhghalam et al., 2014).

Pavement roughness is measured using the International Roughness Index (IRI). The

IRI index measures “... the suspension motion relative to distance traveled.” (Greene et al.,

2013). Various researches were performed in this area, seeking to find the relation between

pavement roughness and IRI. These researches include the work performed by Sandberg

(1990) and Watanatada et al. (1987).

In 1990, Sandberg studied 20 different road surfaces with various road textures. The

tests were performed at various speeds of 50, 60, and 70 km/h. Road types included unpaved

roads, asphalt mixtures, and chip seals. The results of this study indicated that the fuel

32

consumption can vary by 11% from the smoothest to the roughest road. However, this study

did not include concrete pavement, which can be one of the limitations of this study.

Watanatada et al. (1987) performed a study known as the World Bank study. This

study performed a numerical relationship between pavement roughness and fuel

consumption. However, this study had various limitations, which prevented performance of a

full mechanistic model. First, the study could not isolate factors other than pavement

roughness, which affected fuel consumption. It should be noted that various criteria affect

fuel consumption, such as inertial forces, gravitational forces, and air resistance. To fully

model the effects of pavement roughness, all other criteria should be isolated; that isolation

was not performed in this study.

2.3.2.3 Vehicle speed

Other studies proved that when cars speed, the car temperature increases, which in

turn affects fuel consumption. For example, a study performed by Louhghalam et al. (2014)

proved that fuel consumption on asphalt pavement can be doubled at a temperature of 30° C,

compared to the consumption at 10°C. Moreover, this study also proved that when

considering car speed reduction from 80 to 20 km/h, the fuel consumption can increase from

3.5 to 8.1 L/100 km for flexible pavement. However, concrete pavement was not sensitive to

this criterion.

Stubstad (2009) performed a study to measure vehicle fuel economy traveling on

various pavement types. Results found that vehicles travelling on concrete pavements

consumed 2% less fuel. Moreover, other studies showed 1% less fuel consumption between

asphalt and concrete pavement (Stubstad, 2009). A summary of the study performed is

illustrated in Table 5. However, one of the limitations of this study is that the study did not

evaluate pavement texture.

33

Table 5. Factors affecting fuel consumption (Fernando 2006)

Test conducted Fuel reduction

Impact of vehicle speed on PCC 6.5%

(this percent is for each 5 mile per

hour decrease in vehicle speed

Ac vs. PCC Fuel efficiency

van on I-80

1.9% to 3.2%

(for PCC)

PCC pavement with diamond

grinding, resulting in improving

International Roughness Index

(IRI)

1.8% to 2.7%

(this percentage is for every

decrease of IRI by 50 inch/mile)

Impact of tire pressure on PCC

and AC pavement.

1.0% to 1.7%

(this percent is for each 4 psi

decrease in tire pressure)

AC vs. PCC Fuel efficiency

van on I-5

-0.1% to 0.8%

There was no statistical difference

found

In 2009, Sumitsawan et al. performed a research to study the effect of pavement type

on fuel consumption and emissions. This research focused on urban driving, commonly used

in the United States. If there were significant differences in fuel consumption and emissions

rates across various pavement surface types, then urban driving might result in variances in

the total energy consumption during the design life of roadways.

To accomplish this research, fuel consumption measurements were performed using a

vehicle driven over two different types of pavement surfaces: AC and PCC, applying two

driving modes: one with constant speed and the other with acceleration. To separate the effect

of pavement type on fuel consumption, various trials were made to control all factors that

could affect the fuel consumption. These factors include tire pressure, wind speed,

temperature, and atmospheric pressure (Sumitsawan et al., 2009). The two types of road

surfaces had the same geometric characteristics, and the only difference was the type of

pavement. Moreover, both road types had almost the same IRI (174.6 in/mile) for PCC

pavement, and (180.6 in/mile) for asphalt pavement. The average fuel consumption rates are

illustrated in Table 6.

34

Table 6. Fuel consumption for PCC vs. AC (Sumitsawan et al. 2009)

Pavement Fuel consumption

(average)

Testing criteria

PCC, fixed

speed

40.7 Date: 11/7/2008

Temp: 69°F

AC, fixed

speed

42.7 Wind: 7 mph W(tailwind)

Engine status: warm

PCC, with

acceleration

236.4 Tire pressure: 50 psi

Tank level: full

AC, with

acceleration

236.9 IRI (inch/mile):

174.6 for PCC and 180.6

for AC

Longitudinal slope: +1.2%

Results of this study proved that concrete was more economic in terms of fuel

economy at 30 mph with the level of significance at 10 percent. However, there was no

significance in the acceleration mode. This study evaluated only the difference between

concrete and asphalt, without considering the total pavement structure, which may be

considered a limitation.

2.3.2.4 Noise

The noise found in the pavement use phase was due to noise resulting from the

interaction of pavement and tires (AzariJafari et al., 2015). Various researches in this area are

assessed the impact of various pavement material types on noise. For example, the research

conducted in 2005 by Bennert et al. compared the noise from two types of asphalt: Stone

Matrix Asphalt (SMA) and dense graded asphalt. Results of this study proved that the Stone

Matrix Asphalt produced less noise, compared to the dense graded asphalt, showing that in

use, pavement material affects and promulgates noise.

Other research was performed to study the impact of using various types of materials.

In this study, three types of materials were tested for noise annoyance: cobblestone asphalt,

dense graded asphalt, and open asphalt rubber pavement. Results proved that the noise

annoyance level reaches the highest level with the cobblestone pavement, compared to other

materials (Sandberg & Ejsmont, 2002). These studies proved that pavement materials do

35

impact the resulting noise from the passage of vehicles. However, in attempts to model the

noise using LCA software, the study found that data is rarely found, making it difficult to use

pavement LCA software for modeling noise (Weidema et al., 2013). For example, LCA

software Ecoinvent, does not present information about noise, clearly stating that this

information will be included at a later time (Weidema et al., 2013); yet no time frame was

mentioned.

2.3.2.5 Lighting

Lighting is one of the criteria assessed during the pavement use phase. The AASHTO,

as well as other entities, classified road lighting based on road functional classification and

pavement material. Roads were classified into four broad categories from R1 to R4. This

classification is illustrated in Table 7. Studies that incorporate lighting in the use phase

include a study performed by Hakkin and Makela (1996) and Stripple (2001).

Table 7. Road classification (An Informational Guide for Roadway Lighting and

Illuminating Engineering Society of North America 2000)

Class Description Arterial Freeway

R1 Portland cement concrete

12

6 Asphalt with a minimum pf 15%

aggregates composed of brightener

aggregates

R2 Asphalt with a minimum of 60%

gravel

17 9

Asphalt and a minimum of 10%-60%

brightener aggregates

R3 Asphalt surface and dark aggregates 17 9

Asphalt surface and rough texture

R4 Asphalt with smooth surface 15 8

Hakkin and Makela (1996) performed a Finnish study that incorporated lighting into

the use phase. This study used the same classification described in Table 7 for R1 to R4.

However, the study applied some Finnish norms. For example, the study states that R2

pavement for asphalt requires 250 Watts per square meter (Williams, 1981), resulting in a

66% higher lighting for asphalt pavement. In addition, this study proved that during a lifespan

36

of 50 years, asphalt pavement consumes 720 MWh of electricity more than concrete

pavement (Williams, 1981).

Other studies focused on asphalt vs. concrete reflectance. For example, there is a

study performed by Turk et al., averring that when aging, asphalt reflection increases while

concrete reflection decreases. The finding was that with time, both materials can achieve the

same level of reflection (Turk et al., 2014).

This lighting technique should be accounted for in pavement LCA. Moreover, it

should be noted that this lighting technique varies over time, depending on technology

development (Sanetero et al., 2011); therefore, this technology development also should be

accounted for over time. In the future, there might be some technologies achieving the same

lighting level, while consuming less energy. Therefore, the incorporation of lighting into

pavement LCA should account for technology development over time, as well.

2.3.2.6 Leachate

Pavement mixtures results in various runoffs. Therefore, the use of pavements affect

the surrounding environment. Various research studies were performed in this area, in order

to study the environmental as well as the health impact of leachate resulting from pavement

in the use phase. Yet, there is no clear result as to whether pavement leachate affects either

the environment or human health.

Kriech (1990) performed a study to test whether the leachate materials from asphalt

mixtures are dangerous. The author prepared an asphalt mix design and then tested it for

Toxic Characteristic Leachability Procedure (TCLP) by the EPA SW846- 1311 and SW846-

351 method. After that the leachate was tested for metals, volatiles, semi volatiles, organics,

and (Polynuclear Aromatic Hydrocarbons) (PAH) (Kriech, 1990). Surprisingly, the study

came up with the conclusion that metal concentration can leach from pavements to drinking

water. However, the results show to be under the dosage recommended by the EPA (EPA,

37

2004). The results therefore indicate that the leachate imposes no health or environmental

hazards.

Other research performed by Brantley and Townsend (1999) claimed that leachate can

be severe when using Recycled Asphalt Pavement (RAP). The study collected RAP from old

roadways (prior to the year 1999) and found that the samples contained lead above the

drinking water standards required by EPA (Brantley & Townsend, 1999) with metals above

acceptable standards, since RAP may have been exposed to hazardous materials during the

lifecycle.

2.3.3 DESIGN PHASE

The design phase includes processes such as knowledge of the functional and

structural requirements for a pavement design, based on given site conditions (subgrade,

climate, etc.). Afterwards, the pavement structural composition, inclusive of the necessary

materials, are identified. This phase encompasses the processes involved for the design of

new pavement, as well as for maintenance and rehabilitation, incorporating overlays,

reconstruction, and rubblization. The structural design affects factors such as performance

life, construction, durability, and lifecycle cost (Pavement Sustainability, 2014).

One of the methods to perform pavement design is the Mechanistic Empirical

Pavement Design Guide (MEPDG). The MEPDG is a major change for pavement design.

The word “mechanistic” denotes the use of engineering mechanics, leading to a design that

has three components (Knovel, 2008)

• The theory to predict pavement critical pavement responses, such as stresses and strains

and their relation to traffic and climatic conditions.

• Materials description and classifications, which are consistent with the associated theory

• The relationship between critical pavement response and observed distresses, which is

known as the empirical part.

38

The MEPDG follows a set of defined procedures to analyze and design new and

rehabilitated pavements. The MEPDG also uses common design parameters for traffic,

climate, materials, subgrade, and reliability for all pavements design types. In addition, the

MEPDG may be used for the selection of a design and design alternatives. Also, the MEPDG

presents recommendations for the structure used, including materials and layer thickness for

new and rehabilitated pavements. This recommendation is inclusive of a set of procedures to

select various items such as: layer thickness, rehabilitation, foundation improvements, etc.

(Knovel, 2008)

The output resulting from the MEPDG presents the projected distress, as well as the

International Roughness Index, given at the selected reliability level. Therefore, the output is

not a design procedure directly involving the thickness, but an analysis tool that may be used

by the designer in an iterative method. More specifically, the MEPDG may be used to

evaluate a trial design, including a mixture of layer types and layer thicknesses under specific

site conditions, as well as failure criteria, given at a specific level of reliability (Knovel,

2008).

2.3.3.1 MEPDG general design approach

The design mechanism in the MEPDG consists of three steps and many procedures.

There are various sets of inputs that should be included in the design, such as materials,

traffic, and climate inputs. Materials input are a very pivotal part of the design procedure. The

modulus, as a major component of the property, is necessary for all layers included in the

design pavement structure. In addition, the elastic modulus is required for all PCC layers. For

the traffic characterization, the procedure consists of estimating the axle load distribution

applied to pavement structure. The MEPDG requires neither a single axle load (ESAL), nor a

load equivalency factor. Also, the MEPDG permits a special axle configuration in addition to

the standard, single, tandem, tridem, and quad axles (Knovel, 2008).

39

One major improvement for the MEPDG is the consideration of climatic impacts on

pavement design, including materials, responses, and distresses, to be viewed as an

incorporated technique. These impacts are evaluated using the Integrated Climatic Model

(ICM). This ICM is considered a strong, climatic tool for modeling temperature and moisture

for each pavement layer, as well as the foundation. This ICM considers hourly climatic data

in various forms, such as temperature, precipitation, wind, and cloud, as well as humidity

from different weather stations across the United States. Pavement layer temperatures, as well

as moisture predictions, are gathered from the ICM and calculated hourly, and then are used

to estimate material properties for pavement layers, as well as for a foundation over the entire

design life (Knovel, 2008).

The second stage of the design consists of a structural analysis and an estimation of

performance indicators and smoothness. The analysis process is iterative. First, the analysis

starts by selecting an initial design, which could be performed by the designer. The design

analysis then analyzes the pavement responses and distress models over time. The output of

this stage includes material properties, as well as accumulated damage, distresses, and

smoothness. When the design does not meet the criteria at a specified reliability level,

modifications are performed until satisfactory results are met (Knovel, 2008). The third step

is the evaluation of the design, based on a lifecycle cost analysis. This is to guarantee that the

design is economical as well (Knovel, 2008).

2.3.3.2 Shortcoming of the current pavement design method

Yet despite all the previous design inputs used in pavement designs, there is no

pavement design method that incorporates materials sustainability in the design framework,

such as Global Warming Potential. The current pavement design framework is illustrated in

Figure 10. Therefore in case materials, sustainability should be evaluated, and this framework

should be altered (as performed in later chapters)

40

Input

Traffic

Environment

Materials

Load

spectra Temperature

Layer

Subgrade

Trial design

Mechanistic response model

Environmental response

Mechanistic

response

Empirical response models

Damage (fatigue cracking)

Distresses (rutting)

Faulting

Smoothness

Reliability

Performance criteria

Cracking (various types)

Rutting

Faulting, punchouts, others

Smoothness

No

Meets technical criteria?

Select final design

Figure 10. The MEPDG design framework (FWHA 2015)

Yes

41

2.3.4 CONSTRUCTION PHASE

The construction phase includes processes and equipment required for pavement

construction (Pavement Sustainability, 2014). The following stages should be considered

while evaluating the environmental impact in the construction phase: equipment mobilization

and demobilization, equipment use at the site, and transport of materials from the site

to final disposal option. The construction phase should also include traffic congestion related

to construction activities (Pavement Sustainability, 2014)

Various studies discussed the effect of traffic congestion in the construction phase.

Some of the factors affecting traffic congestion in the construction phase include: traffic

volume, hourly traffic distribution, project duration, and the like. Studies that reflect the

effect of traffic congestion in the construction phase include the works performed by

Keoleian et al. (2005) and Chan (2007),

Keoleian et al. (2005) used a tool from the Kentucky Transportation Center to

evaluate traffic delay, and afterward used EPA’s MOBILE6 tool to convert the delay into

various environmental impacts. The study compared two alternatives, concrete and asphalt

pavements. The LCA phases included in the study are: material extraction phase, construction

phase, use phase, and end of life phase. Results proved that traffic delay in the construction

stage can be compared to the materials production phase (which was significant in this

study), with respect to CO2 and energy consumption, in the event of high traffic projects. The

study concludes that with respect to CO2 and energy consumption, the impact of traffic delay

in the construction phase is greater than the impact of all the other phases included in the

study. In addition, the impact of traffic delay becomes greater when traffic growth rate is

included. For example, when the annual traffic growth rate increases from 1% to 2%, traffic

impact increases by 13% and 23%, respectively (Keoleian et al., 2005).

42

In 2007, Chan performed an LCA analysis, incorporating traffic delay. The study

compared two alternatives -- asphalt and concrete pavement. However, this study found

different results from the one performed by Keoleian et al. (2005). Results of this study found

that the material production phase is the most significant phase when compared to other

phases, and that the impact of traffic phase is comparable to the material production phase

(Chan, 2007); in turn, this finding contradicts the results of Keoleian et al., 2005. In addition,

there are various works performed to assess the impact of construction equipment in the

construction phase. This includes the work performed by Stipple (2001) and Chan (2007).

Striple (2001) studied the impact of construction equipment in the construction phase.

In this study, Striple thoroughly presented various types of construction equipment, such as

pavers and excavators. However, despite the thorough description for the construction

equipment, this study did not include the traffic delay resulting from the construction phase,

which could be considered one limitation of this study.

Hovarth and Hendrickson studied the impact of asphalt placement during the

construction phase. This installation process results in bitumen fumes (Hovarth &

Hendrickson, 1998) from unknown health hazards. These fumes cause eye irritation, as well

as carcinogenic health effects. Various studies were performed in several countries to assess

health impacts associated with asphalt fumes, such as the Netherlands, Norway, and Sweden

(Boffetta et al., 2003). The studies tested the impact of exposing workers to bitumen fumes.

Results indicated that workers experienced little lung cancer increase when compared to

others who were unexposed to health fumes. However, more research should be conducted in

this area.

43

2.3.5 PRESERVATION, MAINTENANCE, AND REHABILITATION

The maintenance and rehabilitation phase occurs during the lifecycle of a projectby

applying treatments to an existing pavement to slow the deterioration rate (Pavement

Sustainability, 2014). Pavements with an extended lifetime undergo more maintenance and

rehabilitation activities than those with shorter lifetimes. Maintenance and rehabilitation may

account for a significant fraction of pavement lifecycle impacts. However, the relative

importance of the maintenance and rehabilitation activities depends on the pavement design

life and the maintenance schedule (Pavement Sustainability, 2014).

Various studies were performed to evaluate the environmental impact of the

maintenance and rehabilitation phase. This includes the work performed by Chan (2007),

Stripple (2006), and Athena (2006).

Chan (2007) compared two alternatives: asphalt vs. concrete. The study was performed in the

United States. The study evaluated the impact of energy consumption, as well as greenhouse

gases for both alternatives. The study included the maintenance and rehabilitation phase;

however, it did not evaluate/incorporate the schedules of maintenance and rehabilitation

activities. The study estimates that the energy consumption for flexible pavements in the

maintenance phase reflects 10% of the initial construction (Chan, 2007).

Also, other studies such as Stripple (2006) evaluated the maintenance activities by

detailing types of activities such as milling and patching, but the research defined no clear

maintenance schedule which might have altered the results. The study evaluated both

concrete and asphalt pavements. Results proved that energy consumption for flexible

pavements in the maintenance phase accounts for 40% of the initial construction (Stripple,

2006).

44

Häkkinen and Mäkelä (1996) also analyzed the maintenance and rehabilitation phase.

This study was performed according to the Nordic maintenance and rehabilitation schedule,

making it very difficult to compare to studies performed in the United States.

Also, there are other studies performed by Berthiaume and Bouchard (1999). The

purpose of the study was to compare the performance of concrete vs. asphalt pavement. The

study included the maintenance phase of concrete. However, one of the limitations of the

study was that it not only oversimplified the maintenance activities, but also provided a

minimum of detail. For example, regarding the maintenance activities of concrete, the study

only stated that half of the concrete top layer was changed for maintenance activities, and

provided specific details for the maintenance type.

Moreover, the study of Moureh et al. (2000) included the maintenance phase. The

purpose of the study was to analyze various types of pavement structures, mostly asphalt

pavement. The study assumed that all the alternatives had the same maintenance and

rehabilitation activities and therefore, the phases canceled one another’s activities from the

overall LCA analysis. The assumption that all the alternatives display the same maintenance

and rehabilitation activities was based on the premise that all these alternatives deteriorate at

the same rate, which could not be the case (Moureh et al., 2000). Therefore, this assumption

may be considered as one of the limitations of this study.

Other studies that included maintenance and rehabilitation activities include the work

performed by the Athena Institute in 2006. The study compared concrete vs. AC alternative.

Various structures from each type were included in the analysis. This study was performed in

Canada; therefore, all the data and assumptions performed pertain to the Canadian region.

This study focused on intensive maintenance and rehabilitation activities, such as the use of

new materials as well as overlays. Yet, the inclusions of minor maintenance and

rehabilitation activities such as crack sealing, etc. were not included in the analysis, under an

45

assumption that the activities were insignificant. In this study, the concrete alternative had

various maintenance and rehabilitation activities, including AC overlays that occurred at the

last half of the design life. Moreover, the other concrete alternative went through full

maintenance activities, including full reconstruction at the last year of the design period. As

for the asphalt, the option went through more intensive maintenance activities, which

included asphalt overlays, asphalt milling, and full reconstruction. Results of the maintenance

phase indicated that the asphalt alternative consumed more energy, compared to the concrete

alternative. The study estimated maintenance to be over 120%, compared to the initial

construction (Athena, 2006).

Yet, through analyzing all previous studies, various studies clearly did not include the

maintenance and rehabilitation schedule of the activities. Moreover, some of the studies did

not include minor maintenance and rehabilitation activities, and accounted for only the major

maintenance and rehabilitation activities. These studies occurred in various countries, which

resulted in making an overall comparison for the maintenance activities between countries

without resolution.

2.3.6 END OF LIFE OPTION

The pavement end of lifecycle is defined as “the final deposition and subsequent

reuse, processing or recycling of any portion of a pavement system that has reached the end

of its lifecycle.” The end of life option includes reuse, recycled, or landfill options. For

asphalt pavement, end of life options includes central plant recycling, as well as full depth

reclamation and landfills. The concrete pavement end of life options includes recycling,

reuse, and landfills. However, each end of life option is a pathway requiring a unique

approach to quantify the environmental impact.

A detailed economic and environmental analysis for recycling and reusing pavement

should be performed to quantify various end of life options. For example, pavement recycling

46

is affected by materials transportation, compared to using virgin materials that are directly

transported to the construction site (Horvath, 2003). Important factors to consider are

technology, disposal costs, transportation, application, and quality.

• Technology. Technology determines whether on site or off site recycling would be

better. The on site recycling requires construction equipment. This choice includes both

cold and hot in-place recycling, as well as full depth reclamation. The other option

consists of recycling pavement in a central plant. This would require environmental costs

such as demolition at the job site, as well as crushing, screening, and stockpiling at the

plant.

• Disposal Costs. When disposing recycled materials in a landfill, the total disposal costs

will include demolition, transportation, and landfill tipping fees. These fees range from

$10 to $70 per ton. The range varies widely, even for small distances. However, it is

important to realize that landfill areas are diminishing.

• Transportation. For recycled materials, the necessary transportation can carry a high

environmental burden, as a result of material transportation from job site to landfill, from

job site to a central plant for processing, or from the plant back to the job site.

• Application. Reused pavement may be reused in base layers or surface layers. It can also

be reused in embankments and fills.

• Quality. The original quality of the recycled materials, such as its processing, storage,

and local specifications, determines the final applications. Not only does the quality for

using recycled pavement differ for concrete and asphalt pavement, but the potential

contamination of recycled pavement may limit its use.

One more thing to note about literature review, as related to end of life options: Little

literature review exists about the landfilling option,which seems to be less attractive due to

the economic value associated with recycling. Moreover, landfill areas are already

47

decreasing. As a result, the landfill option becomes less attractive (Rajendran & Gambatese,

2007).

When using the recycling option, the welfares and impacts of recycling should be

divided amongst the manufacturer and the user; this division will involve allocation and

specifically, open loop allocation. Further analysis into literature review, as well as the ISO

14040 Standards for allocation procedure, reveals that allocation does exist in the ISO 14040

Standards; yet the open loop allocation is not defined (ISO, 2006). This resulted in various

literature reviews that proposed various allocation methods; however, none of these methods

are commonly accepted (Sanetero et al., 2011)

For example, in a study performed by Ekvall and Tillman (1997), the objective of the

study was to make the allocation effect oriented, rather than cause-oriented. The study first

defined an allocation based on ISO Standards, as well as the current problems associated with

allocation methods. The authors then proposed eight allocation methods for end of life

(Ekvall & Tillman, 1997). Moreover, the authors concluded that the allocation method is very

specific to each study, depending on the goal and scope of the study. As a consequence, the

study presented no rigid method or theory for allocation, since the findings would be study

specific.

Other studies performed on allocation include the work performed by Nicholson et al.

(2009). The study proposed only five different allocation methods. Moreover, the study came

up with a different conclusion. The study stated that the selection of an end of life option can

impact material selection (Nicholson et al., 2009).

The work performed was related to landfilling and recycling options. As a result,

various work was performed to evaluate the environmental impact of landfill (EPA, 2006),

under the premise that this option was easier to predict, compared to the recycling option.

48

Studies that included the end of life option include the work of Huang et al. (2007), and

Horvath and Hendrickson (1998).

Huang et al. (2007) performed a study on the impact of using recycled materials for

asphalt pavement (Huang et al., 2007). The paper discussed the impacts of using recycled

materials such as glass, tires, etc. as an alternative for virgin materials. The study concluded

that the benefits of landfill option and the use of virgin materials is counteracted by the

negative impacts of leaching that can occur in a landfill (Huang et al., 2007). The study

concluded that the use of recycled materials can be an added advantage, provided that such

use would be used appropriately.

Horvath and Hendrickson (1998) also studied the end of life option. The author first

started by giving statistics for the amount of recycled asphalt vs. concrete materials. He based

his statistics on a survey performed by the Federal Highway Administration: The survey was

performed in 29 highway agencies; the statistics indicated that 80% of removed asphalt was

recycled into highway application , resulting in more than 70 million metric tons of asphalt

not going to landfill per year (U.S. Department of Transportation, 1993). The author then

gave some examples of the applications of recycled asphalt in various Departments of

Transportation.

Results indicated that each Department of Transportation had a different issue with

using the recycled asphalt. For example, the Arizona Department of Transportation had

problems with the uniformity of the recycled asphalt (Horvath & Hendrickson, 1998). The

author concluded that the performance of recycled materials/asphalt for the long term is not

documented, which in itself constitutes a problem. The study then recommends that future

work be required for predicting the long term performance of recycled materials.

49

2.3.7 PAVEMENT LCA CRITICAL REVIEW AND CURRENT GAPS

After presenting a detailed analysis of the existing problems in each phase of

pavement LCA, this section will critically review the previous studies per phase. However,

before a critical review, it should be noted that there are common problems between all

studies that pertain to the performance of LCA.

Each of these studies presents a different system boundary, uses a different functional

unit, and was performed in a different country. Consequently, the use of data pertaining to

each country makes the comparability issue almost impossible across all studies. The

multiple variations make a consistency in comparison unattainable. Moreover, depending on

the goal and scope definition of each study, each author used a different LCA, ranging from

attributional to dynamic to hybrid LCA.

For example, the study performed by Häkkinen and Mäkelä (1996) was performed in

Finland. The author used a process LCA that covered LCA phases included materials,

construction, use, maintenance, and rehabilitation items, and the functional unit used was 1

km.

The study was performed by Park et al. (2003) in Korea. The author used a hybrid

LCA, while the included phases constituted materials, construction, maintenance,

rehabilitation, and an end of life option. The functional unit used was energy consumption.

These differences already rendered a comparison across all studies virtually impossible.

However, the current gaps per phase will be presented in this section.

2.3.7.1 Material extraction phase.

The material extraction is the phase that was mostly included in LCA. In addition, this

is the phase that contributed to the most environmental impact compared to other phases.

Issues related to the material extraction phase mostly revolve around the inclusion/exclusion

50

of the feedstock energy. The inclusion of the feedstock energy, highly alter results, compared

to an earlier lack of inclusion in the analysis. More research is required in this area.

2.3.7.2 Design phase

The major shortcoming in the design phase, when evaluating the MEPDG, is that

there is no evaluation/incorporation of the environmental impact of those materials used in its

framework. More research should be performed to characterize and evaluate the

environmental impact, especially towards helping decision makers in the decision making

process. Pavement design should not be evaluated based on technical performance only, but

should also include the environmental impact.

2.3.7.3 Construction phase

Although the construction phase includes the following criteria: equipment

mobilization and demobilization, equipment usage at the site, and transport of materials from

the site to the final disposal option, the construction phase should also include traffic

congestion, related to construction activities. None of the presented research included all the

criteria. For example, some research focused on equipment use alone, while others focused

on traffic congestion.

Future work should then focus on integrating all the criteria affecting the construction

phase together. Moreover, more work should focus on studying/modeling the impact of

traffic congestion, as traffic congestion is very specific to each project and should not be

generalized to all projects. Also, the construction phase can be ameliorated by using

sustainable construction practices. There are various approaches for a sustainable

construction, such as reducing fuel consumption in construction equipment and operations.

This reduction will have environmental and economic impacts. The environmental impact

may be seen in lower environmental emissions, while the economic impact may be seen in

lower fuel consumption, and therefore lower fuel cost. Also, by reducing construction time,

51

this reduction will lead to less lane closure, and as a favorable consequence, lower vehicle

emissions (FHWA, 2015).

2.3.7.4 The maintenance and rehabilitation phase

Most of the studies did not define the maintenance and rehabilitation activities

occurring in this phase. Moreover, some studies assumed that the performance of all

alternatives remains the same, and therefore the environmental impact of the maintenance

and rehabilitation activities would cancel out one another’s impacts, which is incorrect. It

should be noted that detailed maintenance and rehabilitation activities should be performed

for each design, and the environmental impact should be modeled accordingly.

2.3.7.5 The use phase

Various issues are associated with the use phase. As previously illustrated, factors affecting

the use phase include: pavement structure, pavement roughness, vehicle speed, noise, lighting

and leachate. Each one of these factors needs future research consideration as follows:

• Pavement structure and pavement roughness: Studies rarely characterized the overall

pavement design used in each study. Moreover, not all pavement roughness was taken

into consideration. Future characterization should be performed to model all pavement

types and designs.

• Noise: More research should be performed in this area, as noise was not much included

in the literature review. Also, more information should be put into LCA software in order

for stakeholders to use this information in performing LCA.

• Lighting: More research should be performed in lighting technology. The more the

technology advances in the lighting area, the less energy will be consumed, and therefore

huge energy savings may be achieved while performing an LCA.

• Leachate: More research should be performed to assess the impact of leachate on the

environmental as well as the health system.

52

Moreover, each of the previous factors was modeled separately in the literature review.

For example, some literature reviews studied the impact of noise, while others studied the

impact of lighting, and still others studied the impact of leachate. However, no study

integrated all factors together in a single model. Therefore, the interaction between all these

models does not exist in a combined model.

2.3.7.6 End of life option

Gaps associated with the end of life option include predicting the long term

performance of recycled materials. Moreover, in case of using the recycling option, there

should be proper allocation methods. As illustrated in the past literature reviews, there is no

fixed rule for allocation and to date, this is project specific, depending on the study. More

research should be performed in this area to determine proper allocation methods.

2.3.8 ANALYSIS OF CONCRETE VERSUS PORTLAND CEMENT PRODUCTION

After examining pavement LCA phases in detail for both concrete and asphalt

pavement, more detailed analysis should be performed for concrete. To be more specific, a

comparison will be performed between LCA literature review for concrete and cement, a

component contributing to significant environmental impact during concrete production (8).

The analysis will be performed from cradle to gate and will be focusing on two of the four

LCA stages: scope and goal definition and lifecycle inventory analysis. The objective is to

determine existing limitations and areas requiring future work.

2.3.8.1 Portland cement

Portland cement production is composed of the following stages: extraction of raw

materials, and preparation of raw materials as well as blending, bioprocessing, grinding with

gypsum, packaging, and finally shipping the final product (Innovations in Portland Cement

Manufacturing, 2011). The inclusion of the transportation stage is very important in Portland

cement production, as it occurs over most of cement lifecycle.

53

Literature review reported that the processing part of the Portland cement is the most

energy-intensive part, contributing to 90% of the total energy used in cement production

(Medgar et al., 2007). As for the raw material extraction, this stage is not considered

significant in the whole lifecycle. Despite the fact that this stage does not consume much

energy, the stage nevertheless contributes to high emissions of particulate matter. One more

thing to note here is that the inventory values for raw material preparation, grinding, milling,

and transportation stages are not much provided in literature review, since these stages are

considered negligible (Gorse, 2014). Also, although the impact of each of these stages might

be negligible, the combined group effect might be significant.

Few literature reviews focused on studying different types of cement, such as blended

cement in the United States. In fact, this finding is due to regulations in the United States that

restrict the use of blended cement (Boesch et al., 2010). Therefore, when studying blended

cement in the United States, external data sources should be reviewed.

During the cement production stage, energy is consumed in various forms such as

fuels and electricity. The fuel used depend on the manufacturer and the technology used,

therefore imposing another source of variability from one manufacturer to the other (Oss,

2005). As for electricity, it is used for crushing, grinding, and rotating the kiln. As for the

energy consumption data used during production, these are mostly national averages.

Detailed information about variations in these energy data are not evaluated, which causes

problems for researchers requiring detailed information about energy consumption. As, for

the inventory/data from upstream, in case the clinker is imported, the data from the country of

origin is not taken into consideration. Instead, both domestic and imported clinker are

assumed to be produced using similar technologies (Medgar et al., 2006).

Also, clinker production requires a huge amount of heat requirement. Waste fuel are

used as a provider of heat requirement. These are first prepared before combustion in the

54

cement kiln. The common ware fuel used is tires. These tires require shredding, which is also

a heat intensive process, 45 Kilowatts hour/ton (Boesch et. al., 2010).

The amount of clinker required for cement production can be decreased by the use of

supplementary cementitious materials (SCM) such as fly ash and natural Pozzolans (Cyr,

2013). The use of (SCM) has various advantages such as: reducing the amount of material

going to landfill and reducing the amount of clinker required for the production of cement.

Therefore, these SCM can contribute to lowering the environmental impact as well as the

total cost. The use of natural Pozzolans can reduce up to 25% of cost per cement bag for

contractors. This reduction might also be an incentive to build new infrastructure (Mihelcic

et. al., 2007). In countries such as Philippines, a developing country, the use of pozzolans was

linked to socioeconomic indicators (Harris et al., 2008), therefore contributing to sustainable

development. Also, when studying the strength of blended cements including Pozzolans,

results proved that it is comparable to the use of pure cement until a substitution level of

25% to 60% (Cyr, 2013).

One more thing to note, Portland cement might be blended with other materials such as

Ground Granulated Blast Furnace Slag (GGBFS). Depending on the type of blended material,

the required heat/ energy will vary. For example, the GGBFS is related to higher

environmental impact because it has lower particles and sometimes requires extra drying

requirements. For example, GGBFS requires 95 Kilowatts hour/ton to prepare slag, before

mixing it with GGBFS (Skokie, 2003) and 7 Kilowatts hour/ton for fly ash preparation.

2.3.8.2 Portland cement concrete

At the present, concrete production contributes to more than five percent of Carbon

Dioxide produced annually, due to the production of cement clinker. In 2011, an amount of 3

billion metric tons were produced worldwide (Geological Survey, 2011), contributing to 2.6

billion metric tons Carbon Dioxide (Mehta, 2008). Around half of these emissions result from

55

fossil fuel combustion, because cement Portland cement requires extensive energy at 4 to 5

billion metric tons/ton (Mehta, 2001). The other half goes to the calcination process for

limestone. It should be stated that in general, for 1 million tons of Portland cement clinker,

0.85 ton is emitted to the atmosphere (Cement Industry Energy and CO2 Performance, 2009).

It should be noted that this amount varies by different factors such as technology, location,

and production efficiency (Gursel, 2014). Also, it should be stated that Carbon Dioxide is not

the only emission resulting during concrete production, and that there are other emissions.

It should be noted that concrete is a mixture of various products. Therefore, to study

concrete, concepts such as allocation should be understood (Gorse, 2014). The allocation

procedure should facilitate how the inputs and outputs should be divided among different

products, based on the relationship between these products. However, existing literature

reviews do not employ allocation. The allocation process is either done arbitrarily, or on a

100% basis (Gursel, 2014), leading to biased results. In regard to admixture inclusion, little

literature review focused on admixtures, under the assumption that these are included in

concrete with little percentage (1%), and therefore, their impacts are negligible and not worth

studying (Gorse, 2014).

Also, not all the environmental impacts/emissions were equally examined in literature

review. For example, various literature reviews focused on greenhouse gas emissions, and did

not much focus on other criteria such as Volatile Organic Compounds (VOCs). VOCs are

particulate emitted after the concrete manufacturing process (Gorse, 2014). Therefore, more

research is required in accessing criteria such as VOC’s, especially for concrete containing

chemical admixtures (Environmental comparability of cement and concrete, 2005). Also,

emissions of heavy metals were not much studied in concrete LCA studies (Gorse, 2014),

which requires future research. As for the waste resulting from the manufacturing process,

not all waste types were included in the analysis. Solid and liquid waste from concrete

56

batching and water production were not thoroughly studied and need future research (Gorse,

2014).

To conclude, concrete and cement materials are vital construction materials used

worldwide. Cement from among other concrete constituents, as one of the major contributors

to greenhouse gas emissions, was mostly studied. However, other constituents must be

further studied; this procedure will require proper knowledge of criteria such as allocation.

In addition to these specific drawbacks that occur while performing LCA to evaluate

Portland cement concrete and Portland cement, there are further drawbacks associated with

the use of LCA itself, that are reported in literature review. For example, there is a lack of

application regarding regional and technological variations (Gursel, 2014). This criteria is

really important, since criteria such as footprint, should be evaluated based on local data.

However, what currently exists is that only industry wide average data are provided. This

makes it difficult for a certain company to use, since the factors used pertain to a specific

region, such as the electricity grid (Gursel, 2014).

Other drawbacks related to the application of LCA by various researchers is the use of

different functional units. Although not currently performed, it is highly recommended to use

a functional unit that includes all concrete aspects and properties, for strength and durability.

2.3.8.3 THE DEVELOPMENT OF ENVIRONMENTAL PRODUCT DECLARATIONS

Based on a previous analysis of LCA and its limitations, there should be another

method in place for assessing the environmental impact of a product, as an emerging method

for quantifying the environmental impacts of a product which employs Environmental

Product Declarations (EPDs), or a Type III Environmental Declaration. The overall objective

of EPD is: “the communication of verifiable and accurate information that is not misleading

on the environmental aspect of products and services, to encourage the demand for and

supply of those products and services that cause less stress on the environment, thereby

57

simulating the potential for market driven continuous environmental improvement” (ISO,

14020).

2.3.9 ENVIRONMENTAL PRODUCT DECLARATION METHODOLOGY

Environmental information in EPDs shall be based on procedures and results from a

lifecycle study based on an ISO 14040 series of standards. To date, EPDs have been based on

a lifecycle approach using LCA. This section will explain methodological options for issuing

EPDs. There are various ways for issuing an EPD. The common element between all options

is that these are based on a lifecycle interpretation based on ISO 14040, ISO 14041, and ISO

14043. Yet the routes to a final declaration can vary, depending on the inclusion of items

such as data analysis as well as the inclusion of additional information (ISO 14025:2006).

These routes are illustrated in Figure 11. Existing routes are as follows, according to (ISO

14025:2006):

• Route A: based on lifecycle inventory analysis (based on ISO 14040, ISO 14041, and

ISO 14043)

• Route B: based on lifecycle inventory and lifecycle impact assessment (ISO 14040, ISO

14041, ISO 14042, and ISO 14043)

• Route C: based on lifecycle inventory and lifecycle impact assessment (ISO 14040, ISO

14041, ISO 14042, and ISO 14043), plus any additional analysis of the data. However,

this additional analysis does not follow the ISO 14042.

58

It should be noted that the main purpose of EPDs is to offer measurable

environmental data, which are verifiable and not misleading. Although EPDs do not include

comparative claims, the information may be used to make a comparison between products

(ISO 14025:2006).

A relationship exists between LCA and EPD, as shown in Figure 12; EPDs are the

summary of the data collected in LCA. These are verified by a third party to guarantee

transparency, based on ISO 14025.

2.3.10 CONTENT OF ENVIRONMENTAL PRODUCT DECLARATION BASED ON PCR

It also should be noted that a critical review is used to attest whether the LCA study

performed follows international standards, such as ISO 14040, ISO 14041, ISO 14042, and

ISO 14043. The evaluation process should follow the critical review method of 7.3.3 in ISO

LCA

EPD

Third Party

Verification

Figure 12. LCA and EPD relationship

ISO 14041/Goal and scope definition/Inventory analysis

ISO 14042/Impact assessment

ISO 14043/Interpretation

Alternative methodologies

Additional environmental information (optional)

ISO 14020

Result type III environmental declaration

C B A

Figure 11. Various routes for issuing an EPD (ISO 14025)

59

140:1997. The critical review should validate the scientific and technical soundness of the

LCA performance, i.e., whether the data used is valid and in accordance with the goal and the

scope of the overall study and finally, ensure that the final report produced is transparent.

Moreover, the critical review should also contain information on the content and format of

the external verification (ISO 14025:2006). Table 8 illustrates which items should be should

be included/excluded in the EPD (North American Product Category Rules 2012).

The full system boundary is illustrated in Figure 13. This should limit any

inconsistencies in performing an LCA, when performed by various researchers.

Table 8. Information in/out of PCR (North American Product Category Rules 2012)

Information included in PCR Information excluded from PCR

The name and address of the manufacturer. Production, manufacture, and

construction of buildings and capital

goods

The construction product use and the declared unit

related to the data described

Production and manufacture of

concrete production equipment and

concrete delivery

An identification of the construction product by

name.

Personal related activity, such as

travel and furniture

A list including the product components and the

associated ASTM standards.

Energy and water use related to

company management.

The name of the EPD program used and associated

program operators, including names, addresses,

websites, and logo.

The date the declaration was issued and the period of

validity (5 years)

Raw material supply, inclusive of the following:

extraction, handling and processing of raw materials

used for concrete production, cement, additional

cementitious materials, aggregate (including coarse

and fine), water, admixtures, and any additional

materials or chemicals used.

Transportation: The transportation process includes

the transportation of the materials from suppliers to

the gate of the concrete producer.

Core processes/manufacturing: This process includes

the energy used for storing, batching, mixing, and

Table 8 (cont.)

60

Information included in PCR Information excluded from PCR

distributing concrete and identifies the operating

facility/ concrete plant.

Water used in the mixing and distribution process of

concrete.

61

Waste tires Waste input Waste input

Stone and minerals Quary Quary Quarry/crush raw material Material input Varies Material input Facility construction

Quarry water

Fuel extraction and processing Sort Crush Raw material preparation Processing Processing

Water transportation

Sort By process/ clinker production Handling

Office supplies

Electricity generation

Grinding

Water treatment

Handling and packaging

Ancillary materials

Operations Operations Operations Operations Operations Operations

Emission to air/water

Natural aggregates Crushed aggregates Cement ACM Water Add Mixtures

Figure 13. System boundary based on PCR (North American Product Category Rules 2012)

62

2.3.11 CRITICAL REVIEW OF PRODUCT CATEGORY RULE (PCR)

Although many modifications exist in PCR, improvements are still necessary. For

example, there is a section in PCR called: additional environmental information. This section

presents an opportunity to discuss and align conventional LCA indicators and other indicators

that were seldom treated by LCA methods in the past, such as: biodiversity, land use, impact

on threatened species, toxicity from direct exposure, and working conditions, etc. (Ingwersen

& Stevenson, 2016).

Moreover, PCR does not yet include a consideration for benchmarking (Fores et al.,

2015). PCRs provide no section for data interpretation. Consequently, the resulting EPDs

only provide and report environmental information, with no provision for benchmarking or

interpretation criteria (Fores et al., 2015). Also, PCRs do not provide information on how to

assess site-specific environmental impacts, nor do they assess human health toxicity (Fores et

al., 2015). Another dimension that should be added to PCR is material content, through a

listing of chemicals, or what is termed health product declarations. As a result, this PCR

solely provides guidance on environmental information, and reports no information on either

social or economic aspects (Fores et al., 2015).

Another point to highlight is the scope of the PCR, which only covers a cradle to gate

analysis, rather than the entire lifecycle of the product (from cradle to grave). Given this

scope, it should be noted that the PCR takes only a snapshot of the product lifecycle in order

to analyze it, and therefore durability consideration is not considered. As an example, if a

product offers twice the service life of another alternative, is it a good alternative if it has

75% more initial impacts? This is not currently discussed in the current PCR (Shepherd,

2016).

63

2.3.12 THE USE OF ENVIRONMENTAL PRODUCT DECLARATIONS (EPDS)

Manufacturers and practitioners use EPD for different purposes. Table 9 illustrates

these different purposes (Understanding Environmental Product Declarations). Both

manufacturers and practitioners use EPDs for assessing product transparency. Manufacturers

use EPDs to a) identify product improvement opportunities, b) to help in understanding LCA,

c) to verify product information, and d) to show Carbon footprint reduction. However,

practitioners use EPDs for different purposes, such as in LEED credits, Green Globes credits,

in a comparison of similar products, and to aid in understanding LCA.

Table 9. Use of EPD by manufacturers and architects (Understanding Environmental Product

Declarations)

Manufacturers Practitioners

Product transparency √ √

LEED® credit √

Green Globes credit √

To compare similar products √

To identify product improvement opportunities √

To aid in understanding LCAs √

To validate marketing claims √

To verify product information √

To show Carbon footprint reduction √

2.3.13 USING EPD FOR ACCREDITATION

The green building industry continues to grow at an increasing rate. According to

McGraw‐Hill, the construction industry is estimated to make 48-55% of the non-residential

building market, following 29-38% of the residential building market in 2016. The industry

published the EPDs for products such as wood, and the steel and asphalt industries are

engaged in presenting EPDs as well. Therefore, a similar study/EPD is required for the

concrete industry (NRMCA, 2016).

The LEED vs. 4, Architecture 2030 Challenge for products and the International

Green Construction Code entails that building manufacturers must submit Environmental

Product Declarations (EPDs) to prove the environmental performance of their products

64

(NRMCA 2016). LEED vs. 4 gives two points for projects that can document that 1) The

projects have 20 products/materials with EPDs; and 2) The projects have 50% in cost of their

products, demonstrating lower impacts than the industry baselines through EPDs.

The LEED vs. 4 points are given as follows (NRMCA, 2016):

• Self-declared EPDs are worth ¼ value (not verified by a third party).

• Industry wide EPDs are worth ½ value (verified by a third party). These industry wide

EPDs and industry baselines will allow producers to compare their products against a

baseline.

• Plant-specific verified EPDs are worth full value (verified by a third party).

The scope of the study included 72 ready mix concrete products produced by various

companies. This study was performed in accordance with the requirements of the Carbon

Leadership Forum (CLF) Product Category Rules (PCR) for ISO 14025 TYPE III

Environmental Product Declarations (EPDs) for Concrete vs. 1.1 December 2013 (Athena,

2016).

This EPD project report evaluates the impacts for a range of ready mixed concrete

products. The specifications used are ASTM C94: a) standard specifications for ready-mixed

concrete, b) ACI 318, c) building code requirements for structural concrete, d) A23.1-

09/A23.2-09 (R2014), using concrete materials, methods of concrete construction/test

methods, and standard practices for concrete, e) UNSPSC Code 30111500 ready mix, and f)

ACI 211.1: standard practice for selecting proportions for normal, heavyweight, and mass

concrete (Athena, 2016).

The intended application of this industry wide EPD is Business to Business

communication (B to B). The intended audience is inclusive of architects, engineers,

professionals, LCA practitioners and tool developers, academia, governmental organizations,

and policy makers (Athena, 2016).

65

The regions were divided into the following 8 regions, illustrated in Figure 14:

1. Eastern Region

2. Great Lakes Midwest Region

3. North Central Region

4. Pacific Northwest Region

5. Pacific Southwest Region

6. Rocky Mountains Region

7. South Central Region

8. South Eastern Region

In addition to the previous eight regions, a U.S. national average was produced. Values are

provided in Appendix B. Table 10 illustrates the production data summary for each region,

such as the number of plants, the percentage transit plants, the percentage central mix plants,

the average production, the total production, and the maximum and minimum production.

Figure 14. Industry wide average regions (NRMCA 2016)

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Table 10. The production data summary for each region (NRMCA 2016)

The compressive strength distribution for each region is illustrated in Table 11. The

compressive strength range value was divided into three categories: <=3500, >3500 &

<=5000, and >5000.

Table 11. Compressive strength distribution per region as well as per national average

(NRMCA 2016)

Compressive

strength (psi)

U.S.

national

Eastern

region

Great

lakes

Midwest

region

North

central

region

Pacific

northwest

region

Pacific

southwest

region

Rocky

Mountains

region

<=3500 49% 52% 25% 14% 47% 55% 36%

>3500&<=5000 45% 42% 60% 83% 47% 40% 59%

>5000 6% 6% 15% 3% 6% 5% 5%

2.3.14 BENCHMARKING PROCESS USING EPD

As previously discussed, this industry wide EPD will allow decision makers in the

concrete/or pavement industry to compare their products against a baseline. Based on this

comparison, the decision maker will then be able to evaluate the accreditation status. The

Region U.S.

national

Eastern

region

Great

Lakes

Midwest

region

North

Central

region

Pacific

Northwest

region

Pacific

Southwest

region

Rocky

Mountains

region

Number of

plants

469 59 51 32 19 49 16

% Transit

mix plants

83% 68% 66% 69% 58% 68% 59%

% Central

mix plants

17% 32% 34% 31% 42% 32% 41%

Average

production

(yd3)

47,702

53,984

59,200

30,232

50,654

76,956

48,510

Total

production

(yd3)

22,372,23

3,185,06

3,019,20

967,416

962,432

3,770,84

776,157

Minimum

production

(yd3)

596

1,734

4,690

2,278

1,652

7,561

6,831

Maximum

production

(yd3)

403,143

266,909

267,999

168,000

347,014

403,143

165,575

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benchmarking process, illustrated below, is performed by the National Ready Mix Concrete

Association. For example, a company in Texas was used to benchmark the environmental

impacts of its concrete products with respect to the industry wide average study performed. In

fact, this company has issued its own EPD.

Table 12 illustrates the individual EPD produced by the company for a certain

product, while Table 13 illustrates the industry-wide average study. Values will be illustrated

for GWP, ODP, Acidification Potential (AP), Eutrophication Potential (EP) and

Photochemical Ozone Creation Potential (POCP). Since the State of Texas is located in the

south central region, previously illustrated in Figure 14, the industry-wide average results for

the south central region were selected for comparison. These values are illustrated in Table

11. As may be seen, products produced by this company are higher than the industry-wide

average for the GWP, AP, and POCP values, and are lower for the rest (ODP and EP values).

Table 12. Individual EPD for a certain company

Compressive strength value (psi) GWP ODP AP EP POCP

3000 340 4.15E-06 1.914 0.059 27.1

Table 13. Industry wide average study for the central region

Compressive strength value (psi) GWP ODP AP EP POCP

3000 320.82 8.17E-06 1.10 0.39 22.73

The units are as follows:

• GWP are given in units of kgCO2 eq

• ODP are given in units of kg CFC-11 eq

• AP are given in units of kg SO2 eq

• EP are given in units of kg N eq

• POCP are given in units of kg O3 eq

This was given as an illustration. However when documented, the user can select any other

values for benchmarking..

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2.3.15 EPD AS A TOOL FOR PAVEMENT SUSTAINABILITY QUANTIFICATION

To date, EPDs are not used as a tool to quantify pavement sustainability, due to

reasons discussed above. The most important rationale is that the foundation for building an

EPD must be improved. However, whenever the EPDs are available, these may be used to

assess pavement sustainability (FHWA technical meeting).

2.3.16 IMPACTS OF USING EPD IN A PROJECT

The use of EPD involves more material research than materials that do not rely on

EPDs. The use of EPD forces the designers to look more seriously into LCA information in

EPDs. The use of EPD also increases communication between manufacturers, due to

documentation requirements for the EPD credit. Designers also noticed that the use of EPDs

requires specifications to be written in a different manner than other projects, which do not

require EPDs (Gelowitz & McArthur, 2016).

In general, the specifications are written in an open ended manner, whereby

contractors can choose any manufacturer, provided that the product meets or exceeds the

criteria. Yet when EPDs are used, the specifications must be tighter (Gelowitz & McArthur,

2016).

2.3.17 BENEFITS OF USING AN EPD IN A PROJECT

From a designer’s perspective, the following are some of the advantages of using EPD in a

project (Gelowitz & McArthur, 2016).

• The fact that EPDs represent verified documents about the environmental impacts of a

product

• Using EPDs allows an informed decision about a product

• The use of EPDs provides transparent information about a product

From a contractor’s perspective, the following represent some of the advantages of using an

EPD in a project (Gelowitz & McArthur, 2016).

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• Better transparency in material performance

• Consistency of materials selected through the use of a standard document (ISO

140025:2006).

2.3.18 DRAWBACKS FOR USING AN EPD IN A PROJECT

One drawback for using an EPD in a project includes an upcharge for products with

EPDs. In addition, products sent from further distances means more shipping costs. The

warranties for certain products depend on the use of adhesives that have no EPDs, which in

turn creates a problem for the contractor (Gelowitz & McArthur, 2016).

2.3.19 PROBLEMS FACING EPDS IN THE UNITED STATES

The United States faces many issues for the development and use of Environmental

Product Declarations. First, the current infrastructure is inadequate to support the

development and use of EPD in the United States. Second, there is almost no legislation

requiring the use of EPD in the United States, making the use of EPDs optional. It is highly

recommended that the EPA takes the lead in developing a strong lifecycle inventor (Schenck,

2010). Third, there is no support for product category rules. For a proper development of

LCA, these product category rules should first be well developed (Schenck, 2010).

Currently, EPDs are not used in decision making. There is, however, a tendency to use them

in decision making when these are fully developed.

2.4 SUSTAINABILITY RATING TOOLS

A sustainability rating system is a checklist of sustainability best practices related to a

common metric. This metric is usually a set of points that quantifies best practices in a

common unit. By following this method, all the sustainability best practices (energy saved,

ecosystem, water runoff, etc.) can be assessed in common units (points) (FHWA, 2015).

Presently, there are various rating systems used by the Department of Transportation.

These rating systems have different scopes and different rating score systems. Rating systems

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usually focus on practices that match existing regulations, but remain above the minimum

requirement. Rating systems are criticized most of the time, due to the following: 1) These

are considered to be simplistic, and therefore miss the required details; 2) The rating systems

do not include all the scope for sustainable solutions; 3) There is difficulty in deciding which

items to include/exclude in the analysis (FHWA, 2015). This section will present some of the

sustainability rating tools used in various states.

2.4.1 ENVISION

Envision was developed by the Institute for Sustainable Infrastructure (ISI), with the

cooperation of the Zofnass Program for Sustainable Infrastructure at the Harvard Graduate

School of Design. This rating system rates infrastructure such as water storage and treatment,

energy generation, landscaping, transportations, and information systems. The system was

formed by three organizations: The American Public Works Association (APWA), the

American Society of Civil Engineers (ASCE), and the American Council of Engineering

Companies (ACEC). Envision has 60 sustainability credits that are arranged into five

categories: quality of life (13 credits), leadership (10 credits), resource allocation (14 credits),

natural world (15 credits), and climate and risk (8 credits). The program encourages the use

of lifecycle analysis in planning, designing, construction, and operation in order to improve

project sustainability performance by means of a two-process evaluation system.

2.4.2 GREENROADS

In 2009, GreenRoads was developed by CH2M HILL and the University of Washington. The

model simulates sustainability in highway construction by awarding credits to projects that

incorporate sustainability in design practices. As a model, the guide evaluates sustainability

for new construction, reconstruction, and rehabilitation. It also addresses maintenance and

rehabilitation through an operation and maintenance plan.

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Evaluation criteria are divided into two categories: required and voluntary. Each

project

should meet 11 requirements. These requirements are: Environmental Review Process,

Lifecycle Cost Analysis, Lifecycle Inventory, Quality Control Plan, Noise Mitigation Plan,

Waste Management Plan, Pollution Prevention Plan, Low Impact Development, Pavement

Management System, Site Maintenance Plan, and Educational Outreach (GreenRoads,

2012c).

The voluntary categories include six categories: Environment and Water (8 criteria),

Access and Equity (9 criteria), Construction Activities (8 criteria), Materials and Resources

(6 criteria), Pavement Technologies (6 criteria), and Custom Credits (2 criteria) (GreenRoads,

2012b)

2.4.3 INVEST

INVEST (Infrastructure Voluntary Evaluation Sustainability Tool) is a web based tool for

self evaluation. The analysis covers the full lifecycle of transportation services. INVEST is

divided into four modules that cover the full transportation lifecycle: System Planning for

States (SPS), System Planning for Regions (SPR), Project Development (PD), and Operations

and Maintenance (OM). There are 81 criteria organized by module. The criteria are classified

according to sustainability practices as follows:

• System planning for states: This module includes 16 criteria, plus one bonus criteria that

agencies can score, based on their first three criteria.

• System planning for regions: This module includes 16 criteria, plus one bonus criteria for

which agencies are eligible, based on their first three criteria.

• Project delivery and systems planning and process module: This module includes 17

criteria.

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• Project development module awards (33 criteria); these are generally organized from

planning to design to construction.

• Operations and maintenance module (14 criteria); four of these are focused towards

internal operations and ten are focused towards maintenance and operation of the

highway system.

This rating system does not have a third party evaluator, which leads the FHWA to consider

the rating unofficial. The credit rating system of INVEST is heavily weighted towards the

planning phase of the project, allotting 43% to the system planning, 36% to operations and

maintenance, and 22% to project development (Ramani et al., 2011)

2.4.4 GREENLITES

Another method to evaluate sustainability is GreenLITES, developed by the New York DOT

and launched in 2008. The objective for this tool development was the incorporation of ethics

and sustainability into asset management, a comprehensive program, and capital investment

decisions. Furthermore, this tool integrates ecological, structural, safety, and economic needs

into a transportation decision making process. The program awards up to 175 credit points

under five categories. Rating categories include GreenLITES certified, GreenLITES Silver,

GreenLITES Gold, and GreenLITES Evergreen awards (NYDOT, 2012).

At present, GreenLITES is mandatory for all projects in New York City (Krekeler et

al., 2010). Projects are accessed during the conceptual and design phase. Project stakeholders

and the project team review the score card and determine which items are to be included in

the design. Divisions such as Transportation Maintenance, Traffic, Safety, and Mobility, etc.,

use this rating system as a tool to measure performance (Krekeler et al., 2010). NYDOT is

developing a Pilot GreenLITES to rate regional projects using a triple bottom line (NYDOT,

2010). Credit points are assigned as follows: 33% energy and atmosphere, 27% sustainable

sites, and 23% materials and resources. Since GreenLITES was originally developed for the

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domestic use of NYDOT, this tool is mostly applied in the planning and maintenance phase

of the project. This system is not designated for adoption by other DOTs. The system was

found to have the highest distribution of points for environmental concerns.

Moreover, the sustainability rating tools categorize sustainability into three pillars of

knowledge and assigns weights to these accordingly. However, the weight assignment varies

from one rating tool to the other. Figure 15 illustrates the weight assignment per

software/rating tool. As illustrated, the points are assigned differently to the environmental,

social, and economic impacts.

Figure 15. Sustainability rating tool points distribution (Ramani et al., 2011)

2.5 ENVIRONMENTAL ASSESSMENT

In 1969, the United States Congress passed the National Environmental Policy Act (NEPA)

to establish a National Policy, “... which will encourage productive and enjoyable harmony

between man and his environment; to promote efforts which will prevent or eliminate

damage to the environment and biosphere and stimulate the health and welfare of man; to

enrich the understanding of the ecological systems and natural resources important to the

Nation;” (Environmental Assessment, 2011).

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The National Environmental Policy Act (NEPA) of 1969 urges federal agencies to

perform environmental reviews to evaluate the potential impacts of proposed projects. This

NEPA process asks for coordination between local, state, and federal agencies during the

planning and project development decision making process (FHWA, 2014; LaDOTD, 2014).

The project development stage should consider various alternatives that minimize potential

impacts to the society and the environment. Stakeholders affected by the project can

participate and ask questions about existing alternatives and associated environmental impact

(FHWA, 2014; LaDOTD, 2014).

When the environmental impacts about a certain project are unclear, an

Environmental Assessment (EA) is prepared. This (EA), as a public document, presents

evidence as to whether the current impacts require further analysis (FHWA, 2014; LaDOTD,

2014). The EA should present various alternatives for the existing project. For example,

another NEPA requirement is that federal agencies should consider “all reasonable

alternatives.” The term “all reasonable alternatives” is undefined and very broad. However, it

is well understood that the term “all reasonable” means that all feasible project alternatives

that satisfy the economic, as well as the technical aspects of the project (FHWA, 2014;

LaDOTD, 2014).

Moreover, the Federal Highway Administration set procedure for implementation of the

NEPA process for decision making (FHWA, 2014; LaDOTD, 2014):

• Assessment of the social, economic, and environmental impacts of a product or a service.

• Analysis of a range of alternatives, based on project’s needs.

• Mitigation such as avoidance, minimization, and compensation.

When a project is believed to have a significant impact on the environment, an

Environmental Impact Statement (EIS) should be prepared.

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2.5.1 ENVIRONMENTAL IMPACT STATEMENTS (EIS)

An environmental impact statement is a procedure that describes and analyzes any

suggested action, which would have a significant impact on the environment. EIS should

include the following information: a) a description of an action including the pros and cons;

b) a description of the area that is going to be affected; c) an analysis of the environmental

impacts resulting from the action; and d) an analysis to “reasonable” alternatives to the

action, thus providing ways to avoid the environmental impacts (What is an Environmental

Impact Statement). Environmental impact statements include the following phases: purpose

and need, alternatives, affected environment, environmental consequences, comments,

coordination, and a list of preparers.

2.6 SOCIAL LIFECYCLE ASSESSMENT (SLCA)

The United Nations Environmental Program, in tandem with the Society of

Environmental Toxicology and Chemistry, defined the term “social lifecycle assessment” as a

method to assess the social and socio economic aspects of products and the potential positive

and negative impacts along the lifecycle (Dasmohapatra, 2012). SLCA follows the ISO

14040 framework. However, some aspects might differ or be amplified at each phase of the

study (Social Lifecycle Assessment).

Multiple methods have been developed to assess social impacts of a project, based on

a study performed by Jørgensen et al. (2012). The SLCA is still in development, allowing

many improvements to be performed. The Center for European Policy Studies (CEPS),

together with the evaluation partnership (TEP), launched a study to explain, compare, and

examine different ways to perform a Social Impact Assessment (SIA). Results indicated that

this area is less developed than the economic and environmental area, and therefore is not

widely used.

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2.7 PERFORMANCE ASSESSMENT MEASURES

Performance assessment involves evaluating pavement performance with respect to its

intended function and the specified characteristics required to meet this function.

Performance assessment metrics vary. However, the metrics include the a) traditional

condition and distress rating (e.g., rutting, cracking, and faulting), b) composite condition

rating systems, c) pavement structural capacity, d) material design attributes (thickness,

asphalt content, compressive strength, and gradation), as well as mechanisms to compare

these attributes to expected or design parameters. Most of the time, performance is addressed

with respect to current standards and practices. If the current asphalt pavement is expected to

last 15 years, the values of an alternative surface are determined, based on how the projected

life compares to the standard of 15 years.

Behn identified eight main criteria for good performance measures: to evaluate, to

control, to budget, to motivate, to promote, to celebrate, to learn and to improve (Behn,

2003). Researchers identified that measures should be customized to fit culture and

constraints of each transportation agency. Although transportation agencies do have similar

focus areas, the agencies can use different data collection methods, or different benchmarks.

Therefore, adequate evaluation criteria are required to evaluate performance measures.

Zietsman found 15 features for a good performance measure, consisting of measurability,

relevance, sensitivity to change, and illustrative to trends (Zietsman, 2000). Likewise,

Marsden et al. (2010) collected a set of attributes for good performance indicators (Marsden

et al., 2010). The performance indicators should be a) relevant to organization, b) clearly

defined, c) based on available measurement, d) limited in number, e) timely, f) non-

corruptive, g) statistically valid, h) comparable, i) responsive, j) innovative, and k) capable of

aggregation. Another study, published in a report on environmental sustainability indicators,

provides a comprehensive analysis for selecting performance measures by categorizing the

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measures into the following three categories: 1) representation of reality, 2) monitoring and

operation, and 3) management and policy (Joumard & Gudmundsson, 2010).

2.8 LIFECYCLE COST ANALYSIS (LCCA)

The concept of lifecycle cost analysis dates to 1960 when the American Association of

State Highway Officials (AASHO) introduced the first book on lifecycle cost analysis,

entitled the Red Book. At this stage LCCA was introduced for decision makers to evaluate

projects in the planning phase. In the same year, two projects used LCCA to evaluate two

projects. Later, Winfrey collected data about vehicle operations; to be used during LCCA for

pavement (Winfrey, 1969). After that, the LCCA passed through various stages through a

number of years. In 1972, the AASHO issued a Pavement Design Guide recommending the

use of lifecycle costing in a project. In 1981 the FHWA issued the Pavement Type Selection

Policy Statement. This guide stated that a) decisions should be based on performing a

lifecycle cost analysis; b) Lifecycle cost estimation would become more accurate when

pavement management systems became more advanced, thus enabling an accurate estimate of

lifecycle cost analysis.

In 1984, MSDOT/FHWA issued a guide enhancing Pavement Selection based on Life

Cycle Cost ’84. This guide compared the lifecycle cost analysis of concrete vs. asphalt

pavement built since the year 1960. Results from the analysis estimated that the initial cost of

asphalt pavement was lower than the concrete alternative, which could save money that could

be spent for other purposes. However, this same study estimated that on the long term, the

concrete option has the lowest average lifecycle cost per mile, built since the year 1984.

In 1991, LCCA was mandated by legislative acts and was required during the design

and construction of tunnels, bridges, and pavements (ISTEA, 1991). The FHWA mandated

that the Department of Transportation perform an LCCA for all projects with costs above $25

Million (FHWA, 2004). In 1995, the National Highway System (NHS) mandated that states

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perform a lifecycle cost analysis for projects with a cost of $25 million or more. This was

titled the NHS Designation Act of 1995, Section 303 (Kane, 1996). It is clearly represented in

Section 303 that the performed LCCA should include initial cost, future costs such as

maintenance and rehabilitation, and resurfacing over the entire pavement life. In 1998, the

FHWA Interim Tech Bulletin was published. This interim report established detailed

procedures for performing LCCA. Moreover, it introduced the concept of probabilistic

LCCA. Also, it introduced the foundation for the RealCost software (Walls, 1998).

According to the Transportation Equity Act for the 21st Century (TEA-21), lifecycle

cost analysis is defined as: “… a process for evaluating the total economic worth of a usable

project segment by analyzing initial costs and discounted future costs, such as maintenance,

user costs, reconstruction, rehabilitation, restoring, and resurfacing costs, over the life of the

project segment.” The basic LCCA requires defining a schedule for initial and future

activities, for a specific alternative. After estimating the costs of each of these activities, the

same analysis method should be used to evaluate different alternatives (Van Dam et al.,

2015). LCCA provides a method to measure the economic impact of design, materials,

construction techniques, maintenance stage, and the end of life phase.

2.8.1 NET PRESENT VALUE

The net present value is used to select different design or rehabilitation alternatives

that are believed to provide the same performance, over the same analysis period. The

equation used to calculate the net present value is illustrated in Equation 4.

(4)

Where:

• i = discount rate

• n = year of expenditure

• = present value factor

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Pavement initial cost is defined as the cost that occurs at the start of the project. These

initial costs can be summarized as the cost of the material used in pavement, such as:

shoulders, base, sub-base, pavement drainage, joint seal, and traffic control, etc. (Caltrans,

2013).

The maintenance and rehabilitation items are defined as activities that occur throughout

the project lifecycle (Caltrans, 2013). For rigid pavement, the maintenance and rehabilitation

items include activities such as: cleaning and filling existing longitudinal pavement joints,

cleaning and resealing existing longitudinal and transverse pavement joints, cleaning and

sealing cracks, full depth corner patching of jointed concrete pavement, and partial depth

patching of jointed concrete pavement. These items are discussed in detail as follows:

• Cleaning and filling existing longitudinal pavement joints: This process consists of

removing existing sealant in longitudinal joints and refilling them, based on specifications

and plans. Existing joints and pavement surfaces should be cleaned of current sealant

materials or any debris. Afterward, the joints are cleaned with sand blasting or water to

make certain they are free of dust. The joint should then be completely dry before being

refilled (LaDOTD Standard Specifications, 2006).

• Cleaning and resealing existing longitudinal and transverse pavement joints: This process

consists of removing existing sealant in longitudinal and transverse joints and refilling

them, based on specifications and plans. The same procedure applies as well. Existing

joints and pavement surfaces should be cleaned of current sealants, materials, or any other

debris. Afterward, the joints are cleaned with sand blasting or water to make certain they

are free of dust. The joint should then be completely dry before being refilled (LaDOTD

Standard Specifications).

• Cleaning and sealing cracks: This process consists of cleaning and sealing longitudinal,

transverse, and diagonal cracks in accordance with plan requirements. The minimum

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crack width to be sealed should be 10 mm at pavement surface. Before sealing, cracks

should first be cleaned by sand blast. Cracks are then sealed with a hot sealing. The

specifications of the sealant vary from one project to the other (LaDOTD Standard

Specifications, 2006)

• Full depth corner patching of jointed concrete pavement: This process consists of full

depth removal and replacement of PCC at corner breaks. Locations of these corner breaks

should be indicated in the plans. Deteriorated concrete should be removed with approved

tools, without damage to pavement lower layers (LaDOTD Standard Specifications,

2006)

• Partial depth patching of jointed concrete pavement. This process consists of the partial

depth patching of jointed concrete pavement, according to specifications and plan

(Indiana Department of Transportation, 2011)

• In most of the cases, patches are located in places where concrete shows distresses at the

surface. At this point in time, the decision to patch concrete is taken. However, the

distress may be larger than the one appearing at the surface. Moreover, the surface

distress does not show the depth of the damage at the pavement. Therefore, when the

patching process is performed, it is recommended to continuously check for the sound

concrete and remove the damaged concrete. The check to distinguish sound from

damaged concrete can be performed by dropping a reinforcing bar on the concrete.

Sound concrete will respond by producing a solid sound, while damaged concrete will

respond with a hollow sound. At the end of this procedure, it is really important that only

the sound concrete remains and the damaged concrete would be totally removed. In

performing the partial depth patching, the technician should make certain the removed

concrete is within the limits. (Indiana Department of Transportation, 2011)

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• Full depth patching of jointed concrete pavement. The full depth patching of jointed

concrete pavement is the process of full depth removal and replacement of PCC pavement

with joints at the locations indicated in the plans. A concrete saw can be used to saw the

concrete at the required concrete parameter. Damage resulting from saw cutting should be

repaired, including the damage relating to the saw cut area. The full depth patch starts

from the patch location until sound concrete is found. The bottom of the full depth should

be indicated in the contract (Indiana Department of Transportation, 2011)

2.8.2 EQUIVALENT UNIFORM ANNUAL COST (EUAC)

Should the benefits be the same, even if the analysis period differs, an equivalent

uniform annual cost (EUAC) should be used to evaluate different alternatives. The EUAC

method assumes that activities/strategies are repeated at the end of the analysis period.

Another method recommended by FHWA is to use the same analysis period (generally the

shortest of those being considered) for all alternatives, as well as inclusion of the remaining

value at the end of the analysis period (salvage value, or value of remaining service life) as a

benefit or negative cost at the end of the analysis period.

If benefits should vary among alternatives, such alternatives should not be compared

solely based on cost, and the method should be used for evaluation. If all benefits can be

expressed monetarily, then the benefits can be expressed in the same method as the cost.

This method is called Benefit Cost Analysis (BCA). This method evaluates the ratio of the

discounted benefit to discounted cost. However, a simplistic BCA can lead to a false strategy

selection. Due to simplicity, NPV is preferred over the BCA method.

There are other factors existing in the selection of alternatives that cannot be evaluated

monetarily, such as environmental impacts and safety. Therefore, LCCA is not solely

sufficient for decision making between different alternatives.

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2.8.3 DISCOUNT RATE

It is widely accepted that all future values should be estimated in current dollars and

discounted to present value by using a real discount rate that combines both interest and

inflation rates. For pavement LCCA, the discount rate should reflect historical trends over

long time periods (Van Dam et al., 2015). The equation used to calculate the discount rate is

illustrated in Equation 5.

(5)

Where

• D = Real discount rate

• I int = Real interest rate, %

• I inf= Real inflation rate, %

2.8.4 END OF LIFE ANALYSIS (RESIDUAL VALUE): SALVAGE VALUE VS. REMAINING SERVICE

LIFE VALUE

It is necessary to assign a value (either positive or negative) at the end of the LCC

period to capture either the value of the remaining service life value, or if there is no

remaining service life, the salvage value from pavement structure. This salvage value may be

computed as the value of the existing pavement to serve as a support for an overlay at the end

of the analysis period (i.e., recycling or repurposing the pavement in place). These two

options are mutually exclusive, meaning that no analysis can contain both a salvage value and

a remaining service life value. (Van Dam et al., 2015)

2.8.5 USER COST ESTIMATION

User costs originally occur from vehicle operating costs, such as vehicle wear and

tear, fuel consumption, delay costs, and crash costs. The value of road users cost is a general

debate. Many considerations come into play when calculating user delay costs, such as

vehicle class and trip type. While user costs should be considered in decision making, these

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costs should not be considered in the same LCCA stream as agency costs, for several reasons.

Although various literature reviews exist on this topic, the quantification of user costs is

subject to debate and uncertainty. Computing user costs may be so large as either to delay the

decision process or to drive that decision process toward an option that the agency cannot

afford. Therefore, it is recommended by the FHWA that user costs be weighted differently

than agency costs (Van Dam et al., 2015).

2.8.6 DETERMINISTIC LCCA VS. PROBABILISTIC LCCA

The use of fixed values for all LCCA inputs to produce a single output value is

referred to as the deterministic approach to LCCA. While this approach is very simple and

needs few inputs, it does not account for the variability in actual initial costs and discount

rates over time, or for the uncertainty in timing and costs of planned maintenance and

rehabilitation. In fact, the output of a single value resulting from the analysis may imply a

degree of certainty that may prove to be inappropriate in a conclusion (FHWA, 2010).

Therefore, sensitivity analysis can be performed to determine the accuracy of the results.

A probabilistic approach to LCCA is more realistic. Such an approach uses a

statistical description of the probability distribution of each input value in order to account for

an input associated variability that in turn creates uncertainty in the analysis output. A

distribution of output value simulations is produced to provide users with sufficient

information for understanding the variability of the results, together with the confidence that

can be placed in the analysis. The development of appropriate input value distribution is time

consuming, especially if the required data to input the distributions are not available. The

collection of good pavement cost data, maintenance, and performance activities remain

important for a good LCCA.

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2.8.7 THE APPLICATION OF LCCA BY STATE DOTS

LCCA practices were reviewed in the following states: California, Colorado, Florida,

Georgia, Illinois, Indiana, Michigan, Minnesota, New York, Ohio, Oregon, Pennsylvania,

Texas, Utah, Virginia, Washington, and Wisconsin. Table 14 summarizes the findings in

these states as illustrated (Evans, 2011).

• Six states: California, Colorado, Florida, Indiana, Oregon, and Washington from the

selected states use FHWA’s Real Cost software. The Michigan Department of

Transportation (MDOT) uses AASTHO’s Darwin program.

• Three states developed a custom, software package for performing LCCA: Georgia,

Minnesota, and Pennsylvania DOTs use a custom spreadsheet for performing LCCA

(Evans, 2011). The analysis period is estimated to be 40-50 years in most states.

• Almost 50 % of the states investigated use a discount rate of 4 percent. States such as:

Colorado, Michigan, Minnesota, and Washington use a rate based on recommendations

from the Federal Office of Management and Budget.

• Although FHWA recommends the use of LCCA, the following states do not include user

costs for LCCA: Illinois, Minnesota, New York, Ohio, Virginia, and Wisconsin (Evans,

2011).

Table 14. Selected states’ LCCA tools and parameters (Evans 2011)

State LCCA tool Analysis period

(years)

Discount rate

(percent)

User

costs

include

d California Real Cost 20, 35, 55

4 Yes

Colorado

Real Cost

40

Determined

annually

(OMB)

Yes

Florida Real Cost 40 3.5 Optional

Georgia

Custom

spreadsheet

30, 40

3

Yes

(factor in

weighted

decision

matrix) Table 14 (cont.)

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State LCCA tool Analysis period

(years)

Discount rate

(percent)

User

costs

include

d Illinois Not

specified

45 3 No

Indiana

Real Cost

At least 50 (for

new)

Generally, 4,

though consider a

range of 0 to 10

Yes

Michigan

Darwin

and

custom

software

10 to 20

Determined

annually

(OMB)

Yes

Minnesota

Custom

spreadsheet

35 to 50

Determined

annually

(OMB)

No

New York Not

specified

Range

4 No

Ohio Not

specified

35 Range of 0 to 6 No

Oregon Real Cost 40 (new)

50 (Interstate)

4 Optional

Pennsylvania Custom

spreadsheet

50 4 Yes

Texas Custom

software

30 Not specified Yes

Utah Not

specified

25 to 40 4 (recommended) Yes

Virginia Not

specified

50 4 No

Washington Real Cost 50 4 (based on OMB) Yes

As indicated in Table 14, each state has its own practices in regard to performing an

LCCA, LCCA tools used, the analysis period, the discount rate, and an inclusion of user

costs.

States such as California, Colorado, Florida, Indiana, and Washington use Real Cost

software. States such as Georgia, Minnesota and Pennsylvania use a custom spreadsheet.

Illinois, New York, Ohio, Utah and Virginia do not specify software. The State of Michigan

uses a combination of Darwin and custom software. This custom software is named

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Construction Congestion Cost (CO3); the software’s purpose is to help traffic engineers

evaluate user cost analysis during the pavement selection process. In addition, the State of

Michigan uses a project cost software, which includes stored data for all unit prices, to be

selected by the user. Texas developed its own customized software (Evans, 2011)

Similarly, the analysis period differs from one state to another; states such as

California and Georgia have multiple analyses periods: 20, 35 and 55 years for California,

with 30 and 40 years for Georgia. States such as Colorado and Florida have a design period

of 40 years. States of Illinois, Ohio, and Texas have a single value of 45, 35, and 30 years,

respectively. In Indiana, the minimum analysis period is around 50 years. Other states such as

Michigan, Minnesota, New York, and Utah carry ranges of value with 10 to 20 years, 35 to

59 years, a range of values not specified, and 25 to 40 years, respectively. States such as

Pennsylvania, Utah, and Washington have an analysis period of 50 years (Evans, 2011).

By analyzing the discount rate, most states, such as California, New York, Oregon,

Pennsylvania, Utah, Virginia, and Washington, consider that rate to be 4%. Some states

consider the rate to be 3%, such as Georgia and Illinois. Other states determine the discount

rate annually, such as Colorado, Michigan, and Minnesota. Some states have a range in the

discount rate, such as Indiana and Ohio; states such as Texas have no fixed value (Evans,

2011)

The selection of the discount rate is most critical. A high discount rate will be

positively biased towards projects with a low initial construction and a higher maintenance

cost. A low discount rate will be positively biased towards projects with a high initial cost

and a low maintenance cost (Evans, 2011)

There are states that consider user costs, while other states do not. States such as

California, Colorado, Indiana, Michigan, Pennsylvania, Texas, Utah, and Washington

consider the user cost in their calculations. However, states such as Illinois, Minnesota, New

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York, Ohio, and Virginia do not consider the user costs. States such as Florida and Miami

consider the inclusion of user costs as optional, but states such as Georgia consider user cost

as a factor in a weighted average (Evans, 2011).

The definition of user costs, as a result, varies from state to state. In California, user

costs and agency costs are considered to have the same value. In Florida, the user cost

includes: motorist delay time, accident costs, and vehicle operating costs. In Georgia, user

costs and agency costs are calculated separately and are assumed to be different; therefore,

the costs are never summed together. The user cost value is evaluated separately in a decision

making matrix to evaluate the importance (Evans, 2011).

Each state performs its LCCA, based on special conditions. For example, in the State

of Colorado, the LCCA is performed to compare concrete to asphalt pavement for new or

reconstructed projects with an initial value of $2 million; a comparison is performed for

asphalt and concrete surface treatments with an initial value of more than $2 million, in the

event that both pavement alternatives are considered feasible. The State of Colorado has a

leadership role that incorporates statistical research and experience from a current project in

order to integrate the data into long term plans (Evans, 2011).

The State of Illinois performs an LCCA for both new and reconstructed pavements

with more than 4,750 square yards of pavement and/or pavement, costing more than

$500,000. In the event that the economic analysis for one option shows to be no greater than

10% cheaper, the pavement selection process will be based on alternate bidding (Evans,

2011)

In Indiana, an LCCA is performed when there is more than one alternative. The

LCCA is also performed for new and rehabilitated pavement with a mainline pavement more

than 10,000 square yards. Should two scenarios be evaluated and the net present value is

within 10%, the alternatives are considered the same. In this case, other factors such as: initial

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costs, constructability, work zones, and user costs are applied to make the final decision. The

user costs considered here are inclusive of user delay costs during construction, vehicle

operating and accident expenses, fees, and other spending costs during the lifecycle. Also,

Indiana requires a changing pavement design life in order to test LCCA sensitivity based on

current pavement conditions. This also applies in New York, where a sensitivity analysis is

performed to evaluate the sensitivity of LCCA for a particular variable (Evans, 2011).

In Ohio, an LCCA is performed when more than one feasible alternative exists. When

the lifecycle costs of more than one alternative are within 10% of the lowest lifecycle cost

alternative, these choices are considered to be equal to the lowest alternative. Any of these

equal alternatives may be selected. However, when alternatives are not within 10% of the

lowest alternative, the alternatives are eliminated. If no alternatives exist within 10%, the

lowest cost is selected automatically. When alternatives are not within 10% of the lifecycle

cost of the lowest pavement, the lowest cost alternative is selected (Evans, 2011).

The State of Minnesota considers the remaining life of the pavement. The remaining

life is defined as the “prorated” share of the cost of the latest activity, based on the service

life extending after the analysis period. The State of Oregon performs LCCA when

constructing new pavement with more than one mile, or in the case of major pavement

rehabilitation involving total reconstruction or rehabilitation. Also, an LCCA is performed

when pavement design strategies are less than the minimum value of 15 years (Evans, 2011).

In regard to the State of Pennsylvania, an LCCA is performed for all structural

improvements, with a value exceeding $3 million for total projects costs on the interstate and

$15 million for all other facilities. When comparing two alternatives, both should have the

same analysis period. Also, the LCCA is performed without a separate inflation rate. When

there is a difference of 10%, this is sufficient to determine the type of pavement. It should

also be noted that Pennsylvania depends on historical data to develop LCCA inputs. A

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positive example from Pennsylvania is that the state reached out to the industry, which in turn

increased transparency (Evans, 2011).

The State of Texas uses two different software for performing an LCCA: The Rigid

pavement lifecycle cost analysis (RPLCCA) and the Texas pavement type selection (TxPTS).

The RPLCCA is used to evaluate various pavement designs, together with all the associated

costs over pavement life, and then ranks these according to cost. A performance assessment

model is included in RPLCCA, which evaluates the distress rate for each pavement type.

However, RPLCCA requires many inputs, including factors difficult to determine, such as

emissions, accidents, vehicle operating costs, etc. On the other hand, TxPTS as a tool allows

for the comparison of several pavement strategies, and then ranks these according to their

cost. The TxPTS is similar to RPLCCA, except that the TxPTS needs fewer user inputs and

does not calculate distresses, which renders the tool easier to use. However, it should be

noted that TxPTS includes flexible pavement, while RPLCCA only considers overlays

(Evans, 2011).

Utah uses two manuals for determining LCCA: The Pavement Management and

Pavement Design Manual, and the Lifecycle Cost Analysis. The Utah DOT does not consider

either salvage value or energy costs when evaluating LCCA. Factors that are included,

however, are: funds availability, project specific information such as environmental

conditions, and project specific information. The user costs are evaluated by the regional

pavement engineer (Evans, 2011).

As a practice, the Virginia DOT uses the present worth method to evaluate an LCCA.

However, when design life is not the same, the EUAC method is used. When the performed

LCCA results are within 10%, other factors are evaluated. For the State of Washington, the

user cost considered is associated with user delay, as linked to traffic volumes, construction

periods, etc. However, when one of the alternatives is 15% greater than the other, the least

90

expensive one is selected. When an alternative is within 15% of the other alternative, the

DOT performs an engineering analysis. The State of Wisconsin bases its pavement type

selection on the outcome of an LCCA. The lowest cost alternative is selected. Yet when a 5%

difference occurs between the desired design and the lowest priced one, then Wisconsin

requires more documentation before making a final decision (Evans, 2011).

2.8.8 LCCA IN THE STATE OF LOUISIANA

A Lifecycle cost analysis for the State of Louisiana follows the FHWA’s

methodology, as specified in the interim technical bulletin report. An analysis period of 40

years is to be used for new pavement construction, with an analysis period of 30 years to be

used for overlays (Temple et al., 2004)

The timings of various activities are illustrated in Table 15. The assumptions performed for

rigid pavements consist of patching with joint resealing at year 20. In addition, at year 30

there is additional patching with surface retexturing (Temple et al., 2004). Table 15 may be

used as guidance while performing maintenance and rehabilitation for the State of Louisiana.

2.9 PAVEMENT DESIGN AND SUSTAINABILITY

Sustainability factors were previously explained, together with the environmental and

economic pillars. This section will analyze existing pavement design framework by taking the

MEPDG as an example. The Mechanistic Empirical Pavement design guide previously

illustrated in the design phase may be simplified in Figure 16. The framework, as illustrated

in Figure 16, will be modified later to include the new sustainability criteria.

In regard to the reasons discussed earlier, should the environmental impact of the material

used be assessed, the assessment might lead to discrepancy in the final results if LCA were to

be used., For example, a user might take the functional unit as 1 mile, and another one might

take it as 1 km. Also, the system boundary used may be different from one study to the other,

leading to inconsistent results.

91

Table 15. Maintenance and rehabilitation schedule based on the State of Louisiana (Temple et

al., 2004)

Project Type Alternate Year 0 Year 15 Year 20 Year 30

Interstate

Overlay

Rigid New

bounded

PCC

Overlay

No action Clean/seal

joints

3 patches

per mile

N/A

Flexible New AC

Overlay

Cold plane

and

overlay

No action N/A

Interstate

New

Construction

Rigid New JPC

Pavement

No Action Clean/Seal

Joints

Patch 1%

of Joints

Retexture

Patch 3%

of Joints

Flexible New AC

Pavement

Cold Plane

& Overlay

No Action Cold Plane

& Overlay

Other

Arterial

Joints New

Construction

Rigid New JPC

Pavement

No Action Clean/Seal

Joints

Patch 1%

of Joints

Retexture

Patch 2%

of joints

Flexible New AC

Pavement

Cold Plane

& Overlay

No Action Cold Plane

& Overlay

Start

Perform Pavement Design

Did the design

pass technical

requirements?

End

Yes

No

Figure 16. Old pavement design framework (Current pavement design)

framework

92

Moreover, someone might base the study on data from Europe, while another might apply

data from the United States. Therefore, the use of another tool to evaluate pavement

sustainability is highly necessary.

Depending on a stakeholder, the sustainability measures previously discussed (performance

measure, LCA, LCCA and sustainability rating tools) can be used either apart or together.

However, the use of all sustainability measures together will give a more comprehensive idea

for sustainability, since each component evaluates a specific sustainability criterion (FHWA,

2015) for pavement.

The use of rating tools can be a good criterion to evaluate sustainability, as the rating

systems transform sustainability criteria into a common point system. However, rating

systems tend to sacrifice details when evaluating sustainability. Therefore, rating systems

should be used with precaution (FHWA, 2015).

The use of LCA and LCCA together is a good choice to evaluate the economic as well

as the environmental criteria. However, there remain shortcomings to this assessment, since

the social criteria is not included (FHWA, 2015).

2.9.1 FEDERAL HIGHWAY ADMINISTRATION CURRENT TREND- TYING SUSTAINABILITY

PILLARS TOGETHER

Currently, the Federal Highway Administration is working on a program to integrate the

sustainability criteria. In 2010, the FHWA launched a sustainability pavements program for

advancing knowledge about pavement sustainability practices. This program developed five

deliverables to help transportation agencies implement sustainable pavement practices.

These deliverables include:

• A comprehensive reference document for sustainable pavement design

• A framework for performing pavement lifecycle assessment

• A series of various sustainability topics to cover sustainability

93

• A collection of technical resources on sustainability

• Five briefs, entitled 1) Pavement Sustainability, 2) LCA of Pavements, 3) Pavement

Climate Change, 4) Strategies to Ameliorate Sustainability of Flexible Pavements, 5)

Strategies to Ameliorate Rigid Pavement, as well as various webinars focusing on

sustainability for various pavements lifecycle stages. Goal areas were categorized into

four phases.

Figure 17 illustrates goals 1 and 2. The first goal is targeted at pavement systems. The

first task is to develop a sustainable framework for pavement, as well as to define LCA and

LCCA. The framework should help stakeholders during the decision making process. The

second goal is to provide relevant information associated with LCCA. This will be

accomplished through the provision of relevant LCCA documents for guidance, as well as

associated software such as RealCost software (FHWA, 2017).

Figure 17. FHWA goal areas (goals 1 and 2) (FHWA 2017)

The third goal is to provide training associated with the use of LCA and LCCA. This

is to guarantee that stakeholders are aware of how to use LCA and LCCA, as well as to

promulgate an increased awareness of pavement sustainability. This outreach will be

94

performed through webinars and case studies. The fourth goal is the implementation stage.

The objective of this task is to provide an actual tool for stakeholders to benchmark the

implementation of sustainable design practices. Goals 3 and 4 are illustrated in Figure 18

(FHWA, 2017).

Figure 18. FHWA goal areas (goals 3 and 4) (FHWA 2017)

Moreover, this program is summarized in Figure 19, which ties everything together as

an LCA with required data and policy. In Figure 19, the triangular shape indicates that the

base items are most important, because the upper elements cannot be completed without

fulfilling the base items. Moreover, the elements above the LCA framework indicate those

elements that need work in the context of North America. The bottom of the triangle is based

on a strong framework for LCA, then the figure rises until it reaches the policy level (Dylla,

2016), such as California No. 262. The pyramid illustrates not only the importance of the

data, but also that EPD could be a good source of data to fill in the gaps (Dylla, 2016).

95

Figure 19. Requirements for a successful implementation of LCA (Dylla, 2016)

2.9.1.1 California Policy No. 262

The State of California declared that the devastating impact of the Global Warming

Potential endangers the State of California, and thus there is a need to act to decrease the

Global Warming Potential level. The state also stated that there is a huge amount of

emissions released during the manufacturing and transportation of materials used for

infrastructure projects.

Executive order Number B-30-15 mandates agencies to take into consideration the

Global Warming Potential while planning for infrastructure projects. Moreover, a lifecycle

cost analysis should also be performed to evaluate a project (California Legislation, 2017).

The California Policy No. 262 imposes specific bidding requirements for a project.

The bill is entitled the “Buy California Clean Act.” This act will mandate publishing a

End goal

At present

96

maximum level of Global Warming Potentials for the materials used in a bid. This will be

performed by January 1, 2019. To be a successful bidder, the bidder shall submit an

Environmental Product Declaration for his/her products. The Global Warming Potential for a

specific material should not exceed the limit assigned by the authority at this point in time

(California Legislation, 2017). In 2022, these materials will be checked again for the purpose

of adjusting the Global Warming Potential for a specific material downward; to reflect

improvement in the industry (California Legislation, 2017).

2.10 SUMMARY

This chapter first started by defining LCA as a general concept and then explained its

various phases. After that, it moved to pavement LCA and its associated problems. LCA

problems were explained through the selection of various pavement LCA studies covering all

pavement lifecycle phases.

Results proved that various discrepancies can occur while performing an LCA due to

the following reasons: the selection of a system boundary, the selection of a functional unit,

the selection of data (someone might be using data from Europe and the other might be using

data from the United States, etc.). All these discrepancies lead to incomparable results at the

end.

To solve this comparability issue, EPDs were then discussed. As standardized

documents, with a pre-defined system boundary, These would evaluate the environmental

impact of a product, to solve the problems previously described in LCA.

The chapter then moved to the second sustainability pillar as the social impact, then to

the third pillar as the economic impact. The chapter then presented concepts such as initial vs.

the maintenance and rehabilitation activities for a rigid pavement. After that, the chapter

discussed the time value of money to perform a full lifecycle cost analysis

97

Finally, the chapter analyzed the current pavement design framework to evaluate how

to integrate the previous sustainability factors into the current pavement design framework

and how the current pavement design should be changed to integrate these new sustainability

pillars.

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CHAPTER 3. NEW FRAMEWORK AND ASSOCIATED DATA COLLECTION

PROCESS

3.1 INTRODUCTION

The objective of this chapter is to present the proposed pavement design framework

integrating the new sustainability criteria; and then reveal how this framework differs from

the old framework previously described in literature review. This chapter will also explain the

sustainability data used (composed of two components: an environmental and an economic

one), and the process of data collection for replication.

The data is divided into environmental and economic impact sections. The

environmental impact section is divided into an Environmental Product Declaration (EPD)

which covers the extraction of raw material, as well as transportation of the extracted raw

material to manufacturing. Inventory data used to perform LCA is also included in the

environmental impact section, in order to oversee the transportation impact module from the

manufacturer to the project location. The economic impact is composed of two sections that

present an initial cost (cost occurring at the present time), and a maintenance and

rehabilitation section (future cost through the whole lifecycle of the project). The initial cost,

shown in two sections, displays both the material cost collected from the manufacturer, and

the initial cost which includes equipment, profits, and incorporated overheads.

3.2 EXISTING VS. PROPOSED PAVEMENT DESIGN FRAMEWORK

The current pavement design framework is illustrated in Figure 20. As previously

described and illustrated in the literature review, the current pavement design framework

includes no sustainability criteria; the design is solely evaluated for technical performance.

Therefore, to enable the integration of a new sustainability factor, this current framework

should be changed. Due to the fact that the technical performance of the material is

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important, the sustainability criteria should be evaluated, once the design passes the technical

performance and is safe to use.

The modified pavement design framework is illustrated in Figure 21. As can be seen,

the innovative pavement design incorporates a new sustainability factor (environmental and

economic impacts). Therefore, pavement design will first be evaluated for technical

performance (outside the scope of this work). Having satisfied the technical performance, the

design is then evaluated for environmental and economic impacts, respectively. Iterations

should be performed until the design satisfies both sustainability criteria. When the

sustainability criteria is satisfied, the iterations stop and the design is finalized

Start

Perform pavement design

Did the design

pass technical

requirements?

End

Yes

No

Figure 20. Old pavement design framework (FHWA 2015)

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Figure 21. New pavement design framework

There are various ways to check whether the design satisfies the environmental and economic

criteria. For example:

• The study performed by the National Ready Mix Concrete Association for the industry

wide average can be used to benchmark the environmental impacts. In this case, the

Did the design

pass the

required

sustainability

score?

Perform pavement design (outside scope)

Did the design

pass technical

requirements?

End

Yes

No

Start

Evaluate the environmental (module 1) and economic

impact (module 2)

Yes

No

117

benchmarking criteria will be performed with respect to each region, since the study was

performed for each region. For example, the user might benchmark his product with

respect to GWP for the Eastern region or U.S national average. In this case, the user

would compare the GWP produced by his product to the GWP produced by the Eastern

region, to discover whether the GWP of his product is below or above the average.

• In the event that individual Environmental Product Declarations are available, these also

can be averaged for a certain compressive strength value or mix design breakdown. For

competitive reasons, the stakeholder then can benchmark his product with respect to the

average.

• Moreover, other benchmarking criteria can include emission regulations assigned by a

certain law or mandate. As previously illustrated in literature review for example, various

laws/mandates, such as the California Policy No. 262, will authorize certain emissions

requirements that should not be exceeded.

• For an economic impact, the benchmarking criteria can include a certain project budget

that should not be exceeded, and based on history, can be determined by the stakeholder.

In case the design does not pass the sustainability criteria, a redesign should be

performed. This can be accomplished through various ways:

• A change in the mix design used will, in turn, change the environmental impact as well as

the cost (since each mix design has a specific environmental impact, coupled with the

associated cost).

• A change of manufacturer will alter the transportation distance as well, and therefore will

reshape the environmental impact associated with the transportation module. This will

also rework the cost of the mixes and the environmental impact of the mix itself, since

each manufacturer has a different manufacturing technology. Therefore, the resulting

emissions will be different.

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As previously described, the sustainability factor includes environmental and

economic impacts, and therefore the data is divided into environmental and economic

sections. The environmental impact section is divided into EPD, which covers the extraction

of raw material, as well as transportation from raw material extraction to manufacturing and

manufacturing phases. The process is inclusive of a lifecycle inventory data collection to

perform LCA, which covers the transportation impact from the manufacturer to the project

location.

The economic impact is composed of two sections of initial cost (cost occurring at the

present time), and involves the maintenance and rehabilitation section (future cost through

the entire lifecycle of the project). The initial cost involves two sections: the material cost

collected from the manufacturer, and the initial cost including equipment, profits and

overheads used (collected from the Louisiana Department of Transportation and

Development).

The initial maintenance and rehabilitation costs were collected to perform a lifecycle

cost analysis for the pavement during its entire lifetime (cradle to grave). Figure 22 illustrates

the data breakdown structure, as well as the data description, which will be explained by

module.

Figure 23 illustrates the data use process per lifecycle, as per the scope of the study.

As previously described, the environmental impact section will cover impacts from raw

material extraction to manufacturing, as well as the transportation impact from the

manufacturer to the project location. EPD will cover a) the raw material extraction, b) the

transportation from the raw material extraction to the manufacturing phase, and c) the

manufacturing phase. LCA then will be performed in order to cover the transportation impact

from the manufacturing to project location. The economic impact scope will serve to cover

all of the pavement lifecycle from cradle to grave end of life options. Not evaluating the

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environmental impact from cradle to grave emanates from time limitation; in addition, EPD

only covers a cradle to gate analysis.

3.3 MODULE 1: ENVIRONMENTAL DATA COLLECTION PROCESS

The environmental data presented two data categories: The first data category contained

individual Environmental Product Declarations; the second data category contained inventory

data for the transportation impact module.

3.3.1 MODULE 1A :INDIVIDUAL ENVIRONMENTAL PRODUCT DECLARATIONS DATA

Individual Environmental Product Declarations are the declarations submitted by a certain

company to reflect the environmental performance of its products. The collection process of

these EPD was through: a) internet websites, b) communication with the industry, and c)

product data sheets from companies. These data were stored in an Excel sheet with the

following columns:

1. Company name

2. Location of the company, indicated by the zip code city and state

3. Compressive strength value in psi units

4. Environmental impact columns divided into: Global Warming Potential (kg CO2 eq),

Ozone Depletion Potential (kg CFC-11 eq), Acidification Potential (kg SO2 eq),

Eutrophication Potential (kg N eq), and Photochemical Ozone Creation Potential (kg O3

eq).

5. Lifecycle inventory columns are divided into categories of a) total primary energy

consumption (MJ), b) concrete batching water consumption (yd3), c) concrete washing

water consumption (yd3), d) total water consumption (yd3), e) depletion of non-renewable

energy resources (MJ), f) depletion of non-renewable material resources (kg), g) use of

renewable material resources (kg), h) use of renewable primary energy (MJ), i) hazardous

waste (kg), and j) non-hazardous waste (kg).

120

Figure 22. Data breakdown

121

Figure 23. Data use per lifecycle phase

6. A column indicating the validity/end date of Environmental Product Declarations. This

indicates the expiration date of the Environmental Product Declaration. The validity of

any Environmental Product Declarations is usually five years; these are issued from the

date.

7. Mix composition: the mix design composition is divided into the following columns: a)

Portland cement (lb), b) fly ash (lb), c) slag (lb), d) mixing water (gallons), e) water to

cement ratio, f) coarse aggregates (lb), g) fine aggregates (lb), and h) air (%). This

information was collected from a products data sheet. Also, these are the search criteria

for locating a mix design

8. Mix design total weight (lb) and density

Although parts 1 to 6 are normally found in most EPDs, the mix design breakdown is not

usually found in EPD. To collect a mix design breakdown, companies were contacted for data

sheets. Some EPD columns are illustrated in Tables 16 and 17. The search criteria becomes

the mix design breakdown, as illustrated in Tables 16; the output should display the

environmental impact as indicated in Table 17.

Module 1A: EPD

collection process Module 1B:

Transportation impact

collection process

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Table 16. Sample of EPD

Cement

(lb)

Water cement

ratio

Mixing

water

(gallons)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate

(lb)

492 0.5 246 118 1309 1875

411 0.45 262 176 1346 1840

451 0.43 257 141 1193 1875

441 0.44 261 147 1353 1840

367 0.42 254 244 1202 1840

489 0.41 263 153 1108 1900

526 0.39 267 165 1079 1875

376 0.53 249 94 1433 1900

276 0.43 242 288 1340 1900

Table 17. Mix design breakdown

Product

ID

Zip code Compressive

strength

(Psi)

GWP

(kg CO2

eq)

1597 75149 3000 264.54

1734 75149 4500 288.24

1735 75149 4000 312.71

1738 75149 4400 305.83

1811 75149 4500 259.95

1841 75149 4500 336.41

1899 75149 5000 360.88

3.3.1.1 Data statistics

This section provides an overview of the environmental data used through several

statistical numbers. The EPD data contains products from Texas, Florida, Oklahoma,

California, Washington, and Louisiana. The data is divided into three levels: the Louisiana

Level (includes only the State of Louisiana), the South Regional Level (Louisiana, Texas,

Florida, and Oklahoma), and the National Level (includes all States: Texas, Florida,

Oklahoma, California, Washington, and Louisiana). The search range for each region is

illustrated in Table 18, and the total number of products for each state in illustrated in Table

19.

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Table 18. Search criteria

Data statistics are illustrated in Table 19, indicating the number of products per state.

The total items/products are 2,267 products. As illustrated in Table 19, the highest number of

products is produced by the State of California, followed by the states of Texas, Louisiana,

Oklahoma, Washington, and Florida. The complete data is attached in Appendix A.

Table 19. Number of products per State

Number of products Location

328 Texas

3 Florida

28 Oklahoma

1598 California

253 Louisiana

57 Washington

2267 Total

Table 20 illustrates the number of products produced for each compressive strength

value per state. As illustrated, the State of California is the lone state that produces

compressive strength values of 2000, 2500, 6500, and 7500 psi. The State of Texas is the

only State that produces compressive strength values of 3600, 4400, and 9000 psi. All states

produce compressive strength values of 3000, 4000 and 5000 psi.

Region Boundary Cement

(lb)

Water

(gallons)

Fly ash

(lb)

Slag

(lb)

Fine

aggregate

(lb)

Coarse

aggregate

(lb)

Air

(%)

South

region

Lower 276 207 0 0 1047 1652 0

upper 725 444 336 0 1840 1920 7.5

Louisiana Lower 311 131.43 0 0 689 321 3

Upper 950 316.08 122 0 1737 2006 7

National Lower 253 160 0 0 1047 1652 0

Upper 752 444 336 0 1840 1920 7.5

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Table 20. Number of products produced for each State per compressive strength value

Compressive strength

(psi)

State Number of products produced per State

2000 California 17

2500 California 119

3000 California 264

Texas 35

Florida 1

Washington 1

Oklahoma 3

3500 California 257

Oklahoma 4

Texas 3

3600 Texas 17

4000 California 227

Florida 1

Oklahoma 8

Texas 35

Washington 18

4400 Texas 18

4500 California 217

Oklahoma 7

Texas 72

Washington 1

5000 California 214

Florida 1

Oklahoma 4

Texas 37

Washington 12

5500 California 126

Oklahoma 2

6000 California 76

Texas 36

Washington 21

6500 California 40

7000 California 30

Washington 2

7500 California 12

8000 Texas 34

Washington 2

9000 Texas 39

3.3.2 ENVIRONMENTAL PRODUCT DECLARATION FOR THE STATE OF LOUISIANA

The process of issuing an individual Environment Product Declaration is both time

consuming and very expensive. The cost mostly comes from two processes (NRMCA, 2016):

125

• Conducting an LCA and producing an LCA report, and

• Having the LCA report critically reviewed and verified.

Most companies do not have the expertise to perform an LCA inside the company and

consequently, must hire a consultant (NRMCA, 2016). To date, companies that did not

develop their own Environmental Product Declaration therefore participated in an industry

wide, average Environmental Product Declaration study (NRMCA, 2016).

A survey was performed and distributed to concrete companies in Louisiana to assess

the situation. The survey is attached in Appendix C. Companies were asked to report whether

they had measured an environmental impact or inventory for their products. The results

showed that some five companies participated in the industry wide average study, because an

absence of expertise existed within each company to perform a lifecycle assessment These

five companies, with a total of 16 plants, are presented in Appendix D.

The attached survey was conducted and the results were analyzed. The findings are

described (company names were omitted) as follows. All five companies stated that the

sustainability concept is innovative in Louisiana, and that the essential cause for their

participation in the survey is the LEED credit.

• Company 1. Provided the actual survey they submitted to the National Ready Mix

Concrete Association. They were “very interested in further understanding about this

sustainability concept and the direction that DOTD is trying to go.” The company also

noted that they “would love to be a part of this endeavor” and wanted to “provide further

assistance to this matter.”

• Company 2. Explained that they might issue an individual EPD in a year or so, since

“EPDs are very expensive, time-consuming, and there ... is currently no demand for

them.” However, this company also showed interest in the project, but provided no

specific/individual data for data sensitivity issues relating to the company.

126

• Company 3. Stated that there are many sensitivity issues involved with providing

company specific data; and that there is “no single entity responsible for handling this

matter, and [so] ... many legal issues are involved.”

• Company 4. Explained that the company cannot provide any specific information

regarding their data, due to data sensitivity issues. However, the company highly

encouraged the notion of first issuing an industry wide average study for the State of

Louisiana, “Before going into individual companies’ specific data, you should first start

with an industry wide average study.” The company also stated that they will be issuing

an individual EPD for the company soon (time frame is unknown).

• Company 5. The owner of this company did not reveal any specific data related to the

company. Moreover, the owner’s assistant (who prepared the survey and submitted it to

NRMCA), stated that the company only participated in the survey for the LEED credit

and that the information therein should be kept private.

By analyzing all the previous responses, the survey showed clearly that not only were many

companies concerned about data sensitivity issues, but that also all of the companies had

participated in the industry wide average, solely for the LEED credit.

Furthermore, the consultant (Athena Institute) revealed that the data for the State of

Louisiana was compiled together with other states in the Southern region to produce the

industry wide EPD study. Yet, there exists no environmental impact data/inventory matrix

solely for the State of Louisiana.

To issue an EPD for the state of Louisiana, Portland cement concrete mix designs

were gathered from different LaDOTD districts, in order to assess the environmental impact

per mix design. Each district has a set of plants, serving by geographic location. To ensure

that all the mix designs of the companies participating in the industry wide average are

included in the LCA study, all districts were visited. The nine districts are: 2) Bridge

127

City/New Orleans, 3) Lafayette, 4) Bossier/Shreveport City, 5) Monroe, 7) Lake Charles, 8)

Alexandria, 58) Chase, 61) Baton Rouge, and 62) Hammond. The various districts are

illustrated in Figure 24.

Mix design breakdown data were compiled in an Excel sheet to form a database,

specific for Louisiana, with various search criteria. The scope included mix designs for

highways and roadways projects for the past five years (2012 till 2017). The mix designs

included the following classes B, D, and E (associated with rigid pavement design) and other

classes such as A, AA, AA(M), P, R, S, and M, categorized as structural mixes.

Figure 24. LaDOTD districts (LaDOTD)

These mix designs have no soft copies, are found in hard copies in the districts, and

had to be entered manually into the Excel sheet). The mix design sheets collected from the

districts contain the following information:

• Mix design breakdown

• Type of concrete (or class type): Indicates the type of job in which this concrete product

can be used.

4 5

8 58

61 62

2

3

7

128

• Parish name: Indicates the parish in which the project took place. The study input this

information into the data sheet to illustrate the project location for the user.

• Proposal number: The proposal number is used to link the mix design with the actual

project/specifications. This proposal number was kept in the data sheet for future

reference. In the event the user seeks to track the project, the LaDOTD intranet, as well as

the Falcon website, can provide the data needed.

• Project name: The project name, added into the data sheet, should reflect the name of the

project in which the mix design was used.

• Mix design number: The mix design number is to determine/locate a certain mix design

in a certain project. The rationale indicates that a certain project can have more than one

mix design with the same class type.

• Plant code: The plant code is unique for each plant. For example, a company can have

two plants in the same parish; however, each plant has its own plant code.

The database displays 253 products. The database is provided in Appendix D. Table 21

illustrates some statistics about the number of mix designs per each concrete type, as well as

the intended use, based on the Louisiana Department of Transportation and Development

specifications. Class A, with 29 mixes, presents an intended use for box headwalls and

culverts. Class AA has 14 mixes, with an intended use for bridge repairs. Class AA(M) has a

total of 5 mixes, with an intended use for concrete special finishes. Class B has 104 products,

with an intended use for pavement. Class D has 7 mixes, and an intended use for pavement.

Class E has 21 products, with an intended use also for pavement. Class F has 10 products,

with an intended use for culverts and storm drains. Class M, with 43 products has an intended

use for culverts and drainage structures. Class R incorporates 11 mixes, with an intended use

for stubbing and plugging pipes. Class S shows 4 products, with an intended use for shaft

foundations.

129

Table 21. Concrete classes in the database

Concrete Class Intended use Number of mixes

A Box headwalls culverts 29

AA Bridge repairs 14

AA(M) Special finishes for concrete 5

B Pavement 104

D Pavement 7

E Pavement 21

F Culverts/ storm drains 10

M Culverts/ drainage structures 43

P Precast/concrete roadway barriers 4

R Stubbing and pugging pipes 11

S Shaft foundations 4

3.3.2.1 Compressive strength value

Certain minimum compressive strength values are required for each class type, as per the

Louisiana Department of Transportation and Development standard specification for the

Roads and Bridges manual, found on the LaDOTD website. These specifications are

illustrated in Table 22 for each class type. For example:

• The minimum compressive strength value for Class A is 3800 psi,

• The minimum compressive strength value for class AA is 4200 psi,

• The minimum compressive strength value for Class AA(M) is 4400 psi,

• The minimum compressive strength value for Classes B, D, and E are 4000 psi,

• The minimum compressive strength value for Class M is 3000 psi,

• The minimum compressive strength value for Class P is 5000 psi,

• The minimum compressive strength value for Class R is 1800 psi,

• The minimum compressive strength value for Class S is 3800 psi.

130

Table 22. Concrete classes in the database (LaDOTD)

Concrete Class Minimum compressive strength value

(psi)

A 3800

AA 4200

AA(M) 4400

B 4000

D 4000

E 4000

F 3400

M 3000

P 5000

R 1800

S 3800

However, the actual compressive strength value of these mixes should be higher,

depending on project specifications. An intensive search was performed to collect the

compressive strength value of these mix designs. This process included contacting the

LaDOTD various districts and inquiring about the compressive strength values per proposal

number, as well as contacting the industry/concrete companies and inquiring about the

compressive strength values, either by proposal number or by the mix design breakdown and

project year. The data collection process showing various compressive strength values is

illustrated in Figure 25. Figure 25 also presents the data collection process for compressive

strength values on the Louisiana level. Figure 26 illustrates the compressive strength values

for the collected mixes, as well as the compressive strength distribution. The mixes mostly

fall in compressive strength values of 4230 to 4740 psi and from 5250 to 5760 psi.

Furthermore, Athena Institute was asked to provide the breakdown of the environmental

impact in the Environmental Product Declaration. Results of the environmental impacts, as

well as the inventory data, were divided into three parts:

• A1: Raw material acquisition

• A2: Transportation from the raw material acquisition to the manufacturing phase

131

Figure 25. Data collection process for compressive strength values on Louisiana level

Figure 26. Compressive strength distribution

• A3: Manufacturing

A sample from the Environmental Product Declaration provided by Athena Institute is

illustrated in Table 23. Three parts are shown: A1, A2, and A3 for each mix design. The total

environmental impact is the sum of the parts A1, A2, and A3.

132

Table 23. Environmental Product Declaration sample provided by Athena

GWP A1

kg CO2 eq/yd3

GWP A2

kg CO2 eq/yd3

GWP A3

kg CO2 eq/yd3

GWP Total

kg CO2 eq/yd3

187.02 23.34 7.2 217.56

335.01 27.39 7.2 369.6

204.84 24.07 7.2 236.11

204.82 24.06 7.2 236.08

215.63 25.04 7.2 247.87

314.29 26.55 7.2 348.04

172.1 23.2 7.2 202.5

213.82 23.45 7.2 244.47

204.85 24.07 7.2 236.12

187.34 24.32 7.2 218.86

3.3.2.2 MODULE 1B : TRANSPORTATION IMPACT ANALYSIS DATA COLLECTION

(MANUFACTURER TO PROJECT LOCATION)

An increasing awareness of the importance of the transportation sector for achieving

sustainable development goals becomes evident (Gorham, 2002). Although the transportation

sector is crucial for economic and social development, that development imposes risks on the

environment, such as environmental degradation and air pollution (Gorham, 2002). The

transportation sector consumes 25% of the total commercial energy consumed worldwide, as

well as one half of the total oil produced. Moreover, the demand for transportation services is

expected to increase as economic growth increases and income rises. The growth is expected

to increase by 1.5% in industrialized countries (Gorham, 2002).

In the United States, the transportation sector accounts for 72% of the total GHG

leading to an increase in the average surface temperature. This increasing temperature leads

to climate change such as precipitation patterns, storm severity, and rising sea levels. In

addition, this climate change leads to an increase in the number of glacial lakes, a higher risk

of plant and animal extinction, and a death increase from water floods (Najafi et al., 2010).

Statistics show that Texas emits more GHG than France, and California emits more

GHG than Brazil. To mitigate the GHG impact, some states have adopted local plans to

133

reduce GHG inside their borders. It should be stated that while the federal government is

slow in developing a national policy, there still are states that continue to adopt and redefine

plans (Najafi et al., 2010).

Moreover, the transportation sector accounts for Acidification Potential, mostly from

the sulfur emitted from vehicles (Sulphur Levels in Gasoline and Diesel, 2014). This results

in acid gases, which when released to air cause acid rain, which in turn is absorbed by the

plants, soil, and surface water (Acidification, 2017).

Also, Particulate Matters such as PM2.5 and PM10 are released from the

transportation sector. These Particulate Matters are air pollutants composed of liquid and

solid particles suspended in the air. Particulate Matters, referred to as PM2.5, have a diameter

of less than 2.5 micrometer, while PM10 are Particulate Matters that show a diameter of less

than 10 micrometers. Particulate Matters pose significant health impacts, because these small

particles have the capability to penetrate the respiratory system, thereby causing respiratory

and cardiovascular problems such as asthma and lung cancer (Health Effect of Particulate

Matter, 2013).

As a strategy to mitigate the environmental impact of transportation, this section will

present a methodology to quantify the environmental impact resulting from product

transportation from manufacturer location to project location. The environmental impact of

concrete transportation from the manufacturer to the project location will be evaluated using

three types of trucks: a light duty truck (light commercial truck), a medium duty truck (single

unit truck), and a heavy duty truck (combination truck). Two types of fuel will be evaluated

for each truck type: diesel and gasoline.

Inventory values were collected from United States lifecycle inventory free database.

Corresponding inventory data for each truck type and fuel are illustrated in Table 24 for the

combination truck diesel power (light duty truck). Other inventory values for other truck/fuel

134

types are attached in Appendix E. Detailed calculations for the transportation module are

discussed in Chapter 4

Table 24. Combination truck, diesel power (light duty truck)

Details for Transport, combination truck, diesel powered

Flow Category Flow Type Unit Amount

Outputs

Carbon dioxide, fossil air/unspecified Elementary kg 7.99E-02

Carbon monoxide, fossil air/unspecified Elementary kg 1.27E-04

Methane, fossil air/unspecified Elementary kg 1.29E-06

Nitrogen oxides air/unspecified Elementary kg 5.32E-04

Particulates, < 10 um air/unspecified Elementary kg 9.19E-06

Sulfur oxides air/unspecified Elementary kg 1.76E-05

VOC, volatile organic

compounds air/unspecified Elementary kg 2.63E-05

3.4 MODULE 2: ECONOMIC IMPACT

This section will provide an overview of the data collection process for module 2AA,

the cost associated with the mix design only, as well as for module 2AB, associated with the

material price, the construction price, and the installation price. Figure 27 presents the

breakdown to follow up with this section.

Figure 27. Economic analysis database

135

3.4.1 MODULE 2AA: MATERIAL COST

The material price was collected from the manufacturer. Prices were given in terms of

1yd3. A sample is illustrated in Table 25. As evident, each mix design has an associated cost

per yd3.

Table 25. Module 2AA material cost

Product

ID

Zip code Compressive

strength

(psi)

GWP

(kg CO2

eq)

Cost

($/yd3)

1597 75149 3000 264.5462 212

1734 75149 4500 288.2483 242

1735 75149 4000 312.715 219

1738 75149 4400 305.8338 230

1811 75149 4500 259.9587 217

1841 75149 4500 336.4172 220

1899 75149 5000 360.8839 243

3.4.1.1 Statistics for module 2AA

As previously described, this database contains pavement items in addition to

structural items (non-pavement items). The total number of items is illustrated in Figure 28.

The total initial cost items for the pavement items shows to be 121, whereas the total initial

cost items for the structural elements show a sum total of 154.

Figure 28. Initial cost database data statistics

136

For the paving items, Table 26 illustrates the number of initial cost items per layer

thickness. As illustrated in Figure 29, most of the layer thickness falls in the 8, 9, and 10 inch

categories (three highest values).

Table 26. Number of items in each layer thickness category

Layer thickness

(inch)

Number of items

10 31

11 6

12 9

13 7

14.5 1

14 2

6 1

8.5 1

8 32

9 31

Figure 29. Number of items per layer thickness

3.4.2 MODULE 2AB: OVERALL MATERIAL COST AS PER BID ITEM

This module contains information about bid items (or material cost) including

construction cost, profits, and installation cost. Data for the cost analysis database were

gathered from the Louisiana Department of Transportation and Development. The data are

found online in an Access database format. However, the only database published represents

the past 11 years. Special arrangements were made to get older databases, through specialized

137

personnel working in the Louisiana Department of Transportation and Development. The

data created contains the following information:

• Item number/ID is the same as the item number in the Louisiana Department of

Transportation specifications. This number ID is composed of 11 digits. For the PCC

layer items, the first three digits are 601, while for patching items, the first three digits are

602, etc. A full description of items is detailed in the LaDOTD specification manual.

• Item description: shows, as an example, whether this item is a PCC layer, patching item,

etc.

• Proposal number: uses the proposal number to allow the user to obtain more project

details. This may be accomplished by tracking this proposal number on the LaDOTD

intranet, through the Falcon website.

• Items are categorized based on whether these are initial items, or maintenance and

rehabilitation items. For example, PCC layers were categorized as initial items, as these

are normally the material/mix designs bought at the start of the project. Other items, such

as patching, were categorized as maintenance and rehabilitation items. The classification

process is illustrated in Figure 28. The costs in this database include material price,

profits, overhead, and equipment.

• The cost database was also divided by districts and parishes. The associated cost is made

specific to each district and parish. Since the cost varies based on location, this procedure

guarantees the use of a precise cost, based on the selected parish and district.

• Final column containing costs per corresponding unit of measurement. Various units of

measurements are displayed in the database provided online by LaDOTD, such as ton,

square yards, cubic yards, etc. A special unit conversion was performed to guarantee that

a comparison between items would be performed based on the same unit; for example,

the unit of yd3 for volume. PCC maintenance and rehabilitation items are provided in

138

terms of yd2, while the layer thickness is given separately. The area was multiplied by the

thickness, and the overall cost was adjusted to reflect the cost/yd3.

Tables 27 and 28 illustrate several columns of the cost analysis database. This will be

explained for the reader for replication. For example, Table 27 indicates the proposal ID, as

well as the project name associated with this proposal ID. This will enable the user in reading

the specifications. Then a letting date is illustrated in order to perform the lifecycle cost

analysis later, and to account for the time value of money using the net present value. Then

the parish and district names are provided as well. The cost items for these projects are

illustrated in Table 28. The initial items for these projects consist of Portland cement concrete

with various thicknesses, depending on the design and specifications. The final cost is then

given for per 1yd3 for consistency, to further enable a comparison between products.

Table 27. Initial cost items (project information)

Number Proposal

ID

Proposal description Letting

date

District Parish

name

1 H.000466.6 U.S 190:

roundabout at Eden

church road

5/13/2015 Hammond Livingston

2 H.001205.6 LA 39: la 47-lake

Borgne Canal

Bridge

4/24/2013 New

Orleans

St.

Bernard

Table 28. Initial cost items information (cost items)

Number Item Item description

Type

Bid unit

price per

(yd3)

1 601-01-00700 Portland Cement Concrete

Pavement (11" Thick)

Initial $376.36

2 601-01-00300 Portland Cement Concrete

Pavement (9" Thick)

Initial $380.00

3.4.3 MODULE 2B: MAINTENANCE AND REHABILITATION COST DATA

The maintenance and rehabilitation activities occur during the whole pavement lifecycle. For

the State of Louisiana, the maintenance and rehabilitation cost activities for a certain road are

stored in a database which can be accessed through LaDOTD internet. This database contains

139

all the maintenance and rehabilitation activities accomplished on a certain road since the

initial construction.

Tables 29 and 30 illustrate a sample of the maintenance and rehabilitation cost data

(the data was split into two tables, due to space limitation). Table 29 contains project

information, such as the proposal description, the proposal ID in case the stakeholder wants

to check the specifications, and the letting date, used at a later time to perform the lifecycle

cost analysis. Table 30 contains an items description, and presents the actual maintenance and

rehabilitation items and associated costs.

Table 29. Project information

Number Proposal Id Proposal description Letting date

1 H.000466.6 U.S. 190: Roundabout at

Eden Church Road 5/13/2015

2 H.001205.6 LA 39: LA 47-Lake Borgne

Canal Bridge 4/24/2013

Table 30. Items description

Number Item Item description Unit price

per (yd3)

1

602-05-

01160

Full Depth Patching of Jointed

Concrete Pavement (16.0 square

yards and under) (9" Thick)

$580.00

2

602-05-

02160

Full Depth Patching of Jointed

Concrete Pavement (16.1 square

yards to 48.0 square yards) (9"

Thick)

$500.00

Once retrieved, maintenance and rehabilitation items should be linked to the initial

cost items within a full lifecycle cost analysis. In other words, when the user selects a specific

mix design, the user should be able to perform an analysis of the full lifecycle cost based on

that mix design, which entails listing the initial cost, as well as the maintenance and

rehabilitation costs of items.

As previously discussed, the initial cost items already exist in the database. However,

since the projects selected are drawn from the past five years, these projects show no

140

maintenance and rehabilitation activities. To solve this problem, the compressive strength

value of pavement sections will be matched with the compressive strength value of other

pavement sections from past years. The pavement sections will also have corresponding

maintenance and rehabilitation items, with the assumption that the earlier projects would

have undergone similar maintenance and rehabilitation activities. To be more specific, after

matching the compressive strength value, a similar match can be performed using mix design.

The old database to be matched with the new items contains projects, show various

compressive strength values (covering all the compressive strength values in the recent

database) as well as mix designs associated with these projects. Consequently, the first

filtering criteria could be the compressive strength value and the second one could be the mix

design breakdown. This is to guarantee that the matched compressive strength value is equal

or greater than the recent ones, and therefore is easy to use. The compressive strength value

can be controlled using a tolerance level.

There are various scenarios here when matching the compressive strength values and/or

the mix design breakdown (all depend on data availability):

• Scenario 1. Recent projects are matched with the compressive strength values of older

projects (there is a tolerance value), as well as with the associated mix design. This is

considered the best scenario (with a tolerance as well).

• Scenario 2. Recent projects get matched with the compressive strength value of older

projects, yet the associated mix designs of the older projects do not exist. In this case, the

compressive strength value is the only criteria. This should work as well, but will not be

as specific as Scenario 1.

For example, if the user selected a mix design (mix design A) and an associated

compressive strength of 5383 psi from the EPD database, the initial cost will be drawn

automatically from the database, as previously discussed. However, the project will show no

141

maintenance and rehabilitation cost activities. Using the compressive strength value of 5383

psi, similar projects with the same compressive strength value (including a tolerance) may be

identified, and thus the maintenance and rehabilitation activities may be found. For example,

Table 31 illustrates the projects matching the required compressive strength value of 5383.

All the scenarios are illustrated. For example, when exactly matching the compressive

strength value with the value of 5383, the associated projects do not have a mix design

breakdown in the database. This is the case for various projects as well, such as: H.009572.6,

H.009341.6, H.007265.6, H.006622.6, and H.010396.6. It should be noted that the selected

alternatives will vary based on the tolerance level, and that these values are illustrated as a

guide. Also, the selection will vary, depending on selected projects and data availability.

These projects are matched with a compressive strength value and a mix design

breakdown. All the mix designs are illustrated for Table 32, and range from a cement content

of 414 lb to 437 lb (this range can change, depending on available mix designs). The user

can then select the required mix design breakdown and track the corresponding maintenance

and rehabilitation items. The maintenance and rehabilitation items are illustrated in Table 33.

Table 31. Projects associated with the selected compressive strength value

Number

Compressive

strength value

(psi)

Project ID Mix design

available?

8 5383 H.000792.6 No

9 5560 H.010486.6 No

10 5540 H.009572.6 No

11 5540 H.009341.6 No

12 5540 H.007265.6 No

13 5560 H.006622.6 No

14 5560 H.010396.6 No

15 5555.10 450-91-0077 No

16 5548.5 742-17-0153 No

17 5620.51 455-09-0024 Yes

18 5638 H.007116.6 Yes

19 5893.8 013-06-0034 Yes

20 5947.10 025-06-0027 Yes

21 5821.24 808-07-0035 Yes

Table 31 (cont.)

142

Number

Compressive

strength value

(psi)

Project ID Mix design

available?

22 5707.93 742-06-0016 Yes

23 5532.5 742-06-0074 Yes

As illustrated, various projects can show the same maintenance and rehabilitation items.

Depending on data availability, this study recommends comparison/assumption of

maintenance and rehabilitation activities occurring in the same district and parish, since the

cost varies by location.

3.5 DISCOUNT RATE FOR LIFECYCLYE COST ANALYSIS

To perform a lifecycle cost analysis, the net present value is used. This will involve

calculating the real discount rate, which is composed of the real interest rate and real inflation

rate. Future values for real discount rates were forecast, using interest rates and inflation

rates, using Equation 5 Real Discount Rate (D)

(5)

Where

• D = Real discount rate;

• I int = Real interest rate, %

• I inf= Real inflation rate, %

In regard to this equation, the Federal Highway Administration recommends the use of a

discount rate without regard to the individual values of interest or inflation rate. Neither the

interest rate nor the inflation rate values matter, but rather the differences between the two.

This difference has remained constant (LCCA in pavement design 1998; Economic Analysis

Primer 2003, Guide for the Design of Pavement Structures 1993; Guide for the MEPDG

2004). Therefore, this study will focus on using the discount rate, rather than a consideration

of individual values of interest or inflation rate.

143

Table 32. Matching compressive strength value

Alternative

Proposal ID

Compressive

strength value

(psi)

Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Air

entertainer

(%)

17 455-09-0024 5620.51 420 74 1437 1300 415 26 1.5

18 H.007116.6 5638 424 106 1018 1242 600 31.6 3.5

19 013-06-0034 5893.8 429 107 1275 1599 0 32 4

20 025-06-0027 5947.10 445 110 1589 1400 0 31.9 3.5

21 808-07-0035 5821.24 437 109 1119 1875 0 31.3 4.91

22 742-06-0016 5707.93 437 109 1158 1850 0 30 5

23 742-06-0074 5532.5 414 103 1407 1850 0 29.7 0

Table 33. Maintenance and rehabilitation activities for matching compressive strength (example)

Proposal ID Letting date Item Item description Unit Quantity

Bid unit

price

($) per unit

H.000792.6

6/24/2015

NS-805-

00027

Structural Concrete

Patching Ft2 445 365

H.000792.6

6/24/2015

NS-600-

00220

Saw Cutting Portland

Cement Concrete

Pavement

Ft 2800 5

H.010486.6 9/10/2014 602-02-

00300

Cleaning and Resealing

Existing Transverse

Pavements Joints

Ft 668607 0.69

H.010486.6 9/10/2014 602-05-

02200

Full Depth Patching of

Jointed Concrete Pavement

(16.1 square yards to 48.0

square yards)

Yd2 5151 105

H.010486.6 9/10/2014 NS-600-

00220

Saw Cutting Portland

Cement Concrete

Pavement

Ft 29440 0.5

144

3.6 DATA OUTPUT FROM CHAPTER 3

The purpose of this section is to summarize the output for each module. These data

will be used in Chapter 4, together with detailed equations.

For example, the output of module 1 (environmental impact module) has two different

forms: inventory values reported in terms of kg/ton.km coming from the transportation

module and environmental impacts coming from EPD (kg eq/yd3). Consider that a single

environmental score is required for the environmental impact. Therefore, the data should be

converted into the same units, before summing these together. Therefore, the data will need

some modifications, which will be explained in Chapter 4.

Another example can be seen in module 2 (economic module). The output of this

module is the maintenance and rehabilitation cost value given in the future, as well as the

initial cost given at present. These two values are given in different amounts of time, and

therefore cannot be compared. However, some modifications should be performed to make

the data comparable, with the comparison considered at the same point in time. This process

will be explained in Chapter 4. The requirement means that both scores should be summed

together. Given the fact that these scores are not comparable, some modifications must be

performed. The data output per module is illustrated in Figure 30.

3.7 SUMMARY

This chapter presented data concerning the development of the new framework and a data

compilation process to be used later. The data consist of two modules (module 1 and module

2).

• Environmental data containing a compilation of Environmental Product Declarations.

The database included individual product declarations for those states that had produced their

own Environmental Product Declarations. For the State of Louisiana, based on survey results

performed to date, no company exists which has issued an individual EPD, and only a few

145

companies participated in the industry wide average EPD, with the National Ready Mix

Concrete Association.

• An Environmental Product Declaration was produced for the State of Louisiana with the

aid of Athena Institute, through the use of mix designs data from various districts of the

Louisiana Department of Transportation and Development.

• The EPD was inclusive of transportation data containing substance content and an

evaluation of the environmental impact of the transportation stage, incorporating the

manufacturer to use phase. Vehicles were categorized based on their weights in three

categories: light industry truck, medium duty truck, and heavy duty truck. Also, two fuel

types were included: diesel and gasoline.

• Module 2: Economic data containing the cost data for initial costs and for the costs of

maintenance and rehabilitation items.

All the data previously collected are not in the same format, such as units. Moreover, they

pertain to different points in time. For this reason, the data should be modified to ensure that

the data is equivalent. This will be performed in Chapter 4.

146

Figure 30. Data output per each module

147

3.8 REFERENCES

Acidification. (2017). Retrieved from http://www.ziegel.at/gbc-

ziegelhandbuch/eng/umwelt/wirkkatap.htm

Athena Institute. (2016). A Cradle-to-Gate Lifecycle Assessment of Ready-Mixed Concrete

Manufactured by NRMCA Members – Version 2.0. Retrieved February 7, 2017, from

https://www.nrmca.org/sustainability/EPDProgram/Downloads/NRMCA_LCA_Proje

ctReportV2_20161006.pdf

Average Carbon Dioxide Emissions Resulting from Gasoline and Diesel Fuel.

(2005).Retrieved from

http://www.carbonsolutions.com/Resources/Average_Carbon_Dioxide_Emissions_Re

sulting_from_Gasoline_and_Diesel_Fuel.pdf

Average In Use emissions from Heavy Duty Trucks. (2008). Retrieved from

https://nepis.epa.gov/Exe/ZyNET.exe/P100EVY6.TXT?ZyActionD=ZyDocument&C

lient=EPA&Index=2006 Thru

2010&Docs=&Query=&Time=&EndTime=&SearchMethod=1&TocRestrict=n&Toc

=&TocEntry=&QField=&QFieldYear=&QFieldMonth=&QFieldDay=&IntQFieldOp

=0&ExtQFieldOp=0&XmlQuery=&File=D%3A%5Czyfiles%5CIndex%20Data%5C

06thru10%5CTxt%5C00000033%5CP100EVY6.txt&User=ANONYMOUS&Passwo

rd=anonymous&SortMethod=h%7C-

&MaximumDocuments=1&FuzzyDegree=0&ImageQuality=r75g8/r75g8/x150y150g

16/i425&Display=hpfr&DefSeekPage=x&SearchBack=ZyActionL&Back=ZyAction

S&BackDesc=Results%20page&MaximumPages=1&ZyEntry=1&SeekPage=x&ZyP

URL

Economic Analysis Primer. Publication (2003) FHWA-IF-03-032. FHWA, U.S. Department

of Transportation. Retrieved from

http://www.webpages.uidaho.edu/~mlowry/Teaching/EngineeringEconomy/Supplem

ental/USDOT_Economic_Analysis_Primer.pdf

Estimated National Average Vehicle Emissions Rates per Vehicle by Vehicle Type using

Gasoline and Diesel. (2010). Retrieved September, 2016, from

https://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transport

ation_statistics/html/table_04_43.html

Gorham, R. (2002). Air Pollution from Ground Transportation. Retrieved February 7, 2017,

from http://www.un.org/esa/gite/csd/gorham.pdf

Guide for the Design of Pavement Structures (1993). American Association of State Highway

and Transportation Officials, Washington, D.C. Retrieved from

https://habib00ugm.files.wordpress.com/2010/05/aashto1993.pdf

Guide for Mechanistic–Empirical Pavement Design of New and Rehabilitated Pavement

Structures. Final Report, Appendix C: NCHRP, AASHTO. Retrieved from

onlinepubs.trb.org/onlinepubs/archive/mepdg/2appendices_GG.pdf.

148

Hamilton, Jamie. (1995) "Book Review: Time Series Analysis. James D. Hamilton, 1994,

(Princeton University Press, Princeton, NJ), 799 Pp., US $55.00, ISBN 0-691-04289-

6." International Journal of Forecasting, vol. 11, 01 Jan. 1995, pp. 494-495.

EBSCOhost, doi:10.1016/0169-2070(95)90035-7.

Health Effects of Particulate Matter. (2013). Retrieved from

http://www.euro.who.int/__data/assets/pdf_file/0006/189051/Health-effects-of-

particulate-matter-final-Eng.pdf

Heather L., Lester B. (2016). Lifecycle assessment of Automobile/Fuel options, Mellon

University, Pittsburgh. Retrieved from www.cmu.edu/gdi/docs/lca-of-automobile.pdf

Historical Cost Indexes. (2013). Retrieved from

https://www.rsmeansonline.com/References/CCI/3-Historical%20Cost%20Indexes/1-

Historical%20Cost%20Indexes.PDF

Industry‐Wide Environmental Product Declaration (EPD) and Baselines for environmental

Impacts of Concrete. (n.d.). Retrieved 2016, from

http://www.nrmca.org/sustainability/downloads/NRMCA%20Project%20-

%20Industry-Wide%20EPD%20and%20Baselines%20for%20Concrete.pdf

Life-Cycle Cost Analysis in Pavement Design. Pavement Division Interim Technical

Bulletin. Publication FHWA-SA-98-079. FHWA, U.S. Department of Transportation,

Sept. 1998. Retrieved from

https://www.fhwa.dot.gov/infrastructure/asstmgmt/013017.pdf

Miller, J., & Wagner, V. (2016). US: Fuels: Diesel and Gasoline. Retrieved February 7, 2017,

from http://transportpolicy.net/index.php?title=US:_Fuels:_Diesel_and_Gasoline

Najafi, Fazil, et al. "Effective Environmental Policy toward Reducing Greenhouse Gas

Emissions Produced from Transportation." International Journal of Interdisciplinary

Social Sciences, vol. 4, no. 11, Jan. 2010, pp. 113-131. EBSCOhost,

libezp.lib.lsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=a

9h&AN=66385069&site=eds-live&scope=site&profile=eds-main.

National Ready Mix Concrete Association sustainability (NRMCA) Retrieved November 1,

2016, from https://www.nrmca.org/sustainability/EPDProgram/Index.asp

NRMCA EPD Program. (2016). Retrieved from

https://www.nrmca.org/sustainability/EPDProgram/Index.asp

Ryberg, M, et al. "Updated US and Canadian Normalization Factors for TRACI 2.1." Clean

Technologies and Environmental Policy, vol. 16, no. 2, n.d., pp. 329-339.

EBSCOhost,

libezp.lib.lsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=e

dswsc&AN=000332867800011&site=eds-live&scope=site&profile=eds-main.

Sulphur Levels in Gasoline and Diesel. (2014). Retrieved February 7, 2017, from

http://www.transportation.alberta.ca/Content/docType57/Production/Sulphur-

Levels.pdf

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Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-

Duty Vehicles. (2010). Retrieved December 12, 2016, from

https://www.nap.edu/read/12845/chapter/3

The Natural confusion between Alpha Beta Gamma. (2016). Retrieved from

http://www.scmfocus.com/demandplanning/2011/03/alpha-beta-and-gamma-in-

forecasting/

Tsay, Ruey S. Analysis of Financial Time Series (2010). Hoboken, N.J. : Wiley, ©2010.,

2010. Wiley series in probability and statistics. EBSCOhost,

libezp.lib.lsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=c

at00252a&AN=lalu.4161554&site=eds-live&scope=site&profile=eds-main.

Vehicle technologies market report. (2015). Retrieved January 1, 2017, from

http://cta.ornl.gov/vtmarketreport/pdf/chapter3_heavy_trucks.pdf

150

CHAPTER 4. IMPLEMENTATION

4.1 INTRODUCTION

This section will describe the incorporation process of sustainability data into the newly

developed framework. To accomplish this process, the following steps should be performed:

• Adjusting data from module 1 (environmental impact): The purpose of this section is to

guarantee that the inventory values from the transportation impact, as well as the

environmental data coming from EPD, are comparable. Also, the data coming from the

EPD should be adjusted to accommodate the total design volume.

• Adjusting data from module 2 (economic impact): The purpose of this section is to

guarantee the costs data are comparable at the same point in time.

• Obtaining a final score: In this step the environmental score, as well as the economic

score, should be comparable in order to obtain one final single score.

To perform data modification, the following procedure/background should be recalled

from the literature review section: 1) the framework for pavement design, 2) the lifecycle

inventory and lifecycle impact assessment from the overall LCA procedure, 3) the net present

value for the cost analysis.

The new framework should enable product comparison, as well as benchmarking. For this

reason, Chapter 4 will be divided into two sections: data adjustment for alternative design

comparison, and data adjustment for benchmarking section

4.2 ALTERNATIVE DESIGN COMPARISON MODULE

The purpose of this section is to describe the modification procedure, in the event the

stakeholder wants to compare the environmental/economic impact of more than one

alternative. First the data will be adjusted to guarantee the data is equivalent (has the same

units, and are evaluated at the same point in time, etc.) and finally, alternatives are compared

relative to one another’.

151

The importance of the environmental and economic impacts varies, depending on

stakeholder preference (Lippiatt, 2007). For this reason, the user can assign weights for

economic (EcoW) and environmental impacts (EnvW), depending on their importance. The

sum of both weights should sum to 100. The higher the score may be, the higher the

importance.

4.2.1 MODULE 1: THE ENVIRONMENTAL IMPACT

The purpose of this section is to adjust the environmental data from Chapter 3, as well as to

explain the concept, equations, and science behind the procedure.

4.2.1.1 Part 1A: Adjusting data from EPD

As previously discussed in Chapter 3, the output of Part 1A, or the data coming from EPD, is

the environmental impact. These values are reported in terms of the following unit kg eq/yd3

(or per 1 yd3). However, in case of pavement design, these environmental impacts should be

adjusted to account for the total design layer volume. The total design volume for the

pavement layer is illustrated in Equation 6:

(6)

Where:

• Lv = layer volume

• LT = layer thickness

• LW= layer width. The design width in this study is: 12 feet which is the standard road

width

• LL = layer length. The design length taken in this study is: 1 mile

Please note the units in Equation 6, to make certain the units are consistent. This study

recommends having the final layer volume in terms of yd3, since the impacts in EPD are

reported in terms of 1yd3. However, the user might also use units of 1m3 as long as

152

calculations are consistent throughout the study. The conversions used are illustrated in Table

34

Table 34. Unit conversion

Unit Conversion to yard

1 mile 1760

1 inch 1/36

1 feet 0.33

To obtain the total environmental impact per design layer volume, Equation 7 should be used

to convert impacts in EPD, given per unit of volume (1yd3) or (1m3), depending on the

manufacturer, to the total environmental impacts result for the total layer volume.

(7)

The output of Equation 7 should be the environmental impact adjusted per volume.

One more thing to note here, the environmental impact/inventory values are reported in terms

of compressive strength value in EPD. In other words, to find the environmental impact of

any mix design, the search criteria should be in terms of compressive strength value.

Sometimes, the design is given in other properties, such as the modulus of rupture

(this will be discussed later in case studies; for example, rigid pavement design in the State of

Louisiana is reported in terms of modulus of rupture). In this case, the modulus of rupture

should be converted to compressive strength value, to find the impacts from EPD. Various

equations were reported in literature to convert from modulus of rupture to compressive

strength value. For example, the American Concrete Institute Committee (ACI 330), as a

guide for design and construction of concrete, presented Equation 8, relating the modulus of

rupture to compressive strength value.

(8)

Where:

• MOR: is the modulus of rupture

• fc: compressive strength value

153

4.2.1.2 Normalization

Normalization is used to express the impact indicators in a manner that can be compared

among impact categories (EPA, 2006). This process occurs by dividing the indicators by a

selected reference value. Various reference values can be used such as:

• The total emissions or resource use for a given area. These emissions can be either global,

regional, or local

• The total emissions or resource use given for a certain area per capita

• The ratio of one alternative to the other

• The highest value between all alternatives

This study uses the total emissions given per capita. Normalization values are illustrated

in Table 35. All values are extracted from TRACI, except for the fossil fuel depletion and the

renewable energy consumption values, extracted from the Statista database.

Table 35. Normalization value used (Traci and Statista database)

Name (units) Value (impact per

person per year)

Global Warming Potential (kg CO2 eq) 24000

Ozone Depletion Potential (kg CFC-11 eq) 0.16

Acidification Potential (kg SO2 eq) 91

Eutrophication Potential (kg N eq) 22

Photochemical Ozone Creation Potential (kg O3 eq) 1400

Fossil fuel depletion (MJ surplus) 288572.50

Renewable energy consumption (MJ) 24874.5

Values can be normalized using Equation 2 (Stranddorf et al., 2005).

Equation for normalization (previously described as Equation 2):

By analyzing values in EPD for a random mix design (for a total volume of 1 yd3), the

corresponding GWP = 346 kg CO2 eq and the ODP = 3.99E-06 kg CFC-11 eq, which means

these are not on the same scale or units. However, by normalizing them and using

corresponding values given in Table 35, the values then become:

154

Normalized value for GWP = 346 kg CO2 eq/24000 kg CO2 eq = 0.0144

Normalized value for ODP = 3.99×10^(-6) CFC-11 eq/ 0.16 kg CFC-11 eq = 2.49 × 10-5

(Stranddorf et al., 2005) Also, the values become unitless, which facilitates the process of

adding them together later, since the objective is to get one final sustainability score at the

end.

4.2.1.3 Weighting

The weighting process for LCA is the process of assigning weights to various impact

categories, based on their importance (EPA, 2006). This weighting procedure is important,

since it reflects the stakeholder preference. The weighting procedure could be different

depending on stakeholders, and therefore, the reason for assigning any weights should be

documented (EPA, 2006). The weighting criteria used in this study will be based on the

EPA’s weights, as well as the BEES model weights. It should be noted that this study does

not evaluate all the impacts evaluated in the EPA, and only uses the following values: GWP,

ODP, AP, EP, POCP, non-renewable energy consumption, and renewable energy

consumption. Therefore, the weights were scaled to sum up to 100. Table 36 illustrates the

weights assigned by the EPA’s Science Advisory Board criteria, and Table 37 illustrates the

weights used in the study, based on the EPA’s weights.

Table 36. EPA’s Science Advisory Board weighting criteria (EPA, 2006)

Impact category Relative importance (weight) in %

Global Warming 16

Acidification 5

Eutrophication 5

Fossil Fuel Depletion 5

Indoor Air Quality 11

Habitat Alteration 16

Water Intake 3

Criteria Air Pollutants 6

Smog 6

Ecological Toxicity 11

Ozone Depletion 5

Human Health 11

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Table 37. Adjusted weights based on EPA’s Science Advisory Board

Weights EPA Science Advisory

Board Based

GWP 35%

ODP 10%

AP 11%

EP 10%

POCP 12%

NRE 11%

RE 11%

Total 100%

Moreover, the weights for the BEES are illustrated in Table 38; Table 39 illustrates

the weights used in the study based on the BEES model.

Table 38. BEES stakeholder panel judgement (Lippiatt 2007)

Impact category

Relative

importance

(weight) in %

Global Warming 29

Acidification 3

Eutrophication 6

Fossil Fuel Depletion 10

Indoor Air Quality 3

Habitat Alteration 6

Water Intake 8

Criteria Air Pollutants 9

Smog 4

Ecological Toxicity 7

Ozone Depletion 2

Human health (Cancerous Effects) 8

Human health (Noncancerous

Effects)

5

Table 39. Adjusted weight based on BEES

Weights BEES stakeholder

panel

GWP 45%

ODP 3%

AP 5%

EP 10%

POCP 5%

NRE 16%

RE 16%

Total 100%

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This weighting process is performed after values are normalized. The equation used

for weighting was previously illustrated as Equation 3 (Stranddorf et al., 2005). The reason

for repeating the equation here is to display where to use the assigned weights.

Where:

• The assigned weights are illustrated in Tables 37 and 39.

Example, to weight the previous normalized value for the GWP, using the EPA weight, this

will lead to the following value, and the final value become unitless.

Weighted impact = 0.29× 0.0144 = 4.176 × 10 -3

4.2.1.4 Part 1B: Adjusting data: Transportation impact module (Manufacturing to project

location)

As previously discussed, data for the transportation module was extracted from U.S lifecycle

inventory database, a free database available online. These values, illustrated in Table 40, are

the inventory values reported in terms of kg/ton.km, and therefore need to be transformed

into environmental impacts by means of the following: 1) multiplying by the total weight

transported, 2) multiplying by the total distance traveled, 3) characterization of the results.

Table 40. Re-analyzing values for combination truck diesel power for light duty truck

(TRACI)

Details for Transport, combination truck, diesel powered

Flow Category Flow Type Unit Amount

Outputs

Carbon Dioxide, fossil air/unspecified Elementary kg 7.99E-02

Carbon Monoxide, fossil air/unspecified Elementary kg 1.27E-04

Methane, fossil air/unspecified Elementary kg 1.29E-06

Nitrogen Oxides air/unspecified Elementary kg 5.32E-04

Particulates, < 10 um air/unspecified Elementary kg 9.19E-06

Sulfur Oxides air/unspecified Elementary kg 1.76E-05

VOC, volatile organic

compounds air/unspecified Elementary kg 2.63E-05

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The total weight transported consists of two components: truck weight, as well as the

transported concrete. Truck weights for various truck types are illustrated in Table 41.

Table 41. Truck weight by class type (Caltrans 2017)

Type of truck Weight (lb) Weight (ton) Categorization

Light 8000 3.62 Light duty truck

Single unit 20000 9.07 Medium duty truck

Combination 80000 36.28 Heavy duty truck

As for the transported concrete, the total weight of concrete transported should be

calculated. The EPD database previously described contains the density for each mix design,

given in units of mass/volume (lb/yd3). To convert these values into units of mass, the density

values should be multiplied by the total volume of concrete transported/designed. Equation 9

should be used to convert density to mass:

(9)

Where:

• M = Mass (mass of concrete transported)

• D = Density of concrete transported (lb/yd3)

• Lv = Volume. This should be the total volume to be designed, previously calculated in

Equation 6

To get the total number of loads required, per total job, the weight of concrete should be

divided by the maximum truck loading capacity. This can be performed by using Equation

10.

( (10)

The loading capacity for each truck type is illustrated in Table 42.

Table 42. Maximum loading capacity per truck type (Technologies and approaches to

reducing the fuel consumption of medium and heavy duty vehicles 2010)

Vehicle Type Light duty truck Medium duty truck Heavy duty truck

Maximum loading

capacity(lb)

3700 11500 54000

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Equation 11 should then be used to get the total emissions after adjusting per distance

traveled, total weight to be transported, and total number of loads.

× total number of loads (11)

Where:

• The factor of 2 accounts for the backhaul distance.

• Emission of each truck should be taken from Table 40, depending on truck type and fuel

used.

• For truck weight and concrete weight, the truck weight should be taken from Table 41

and the weight of the concrete transported should be added from Equation 9 (density

values are already in the database for each mix design).

• The total distance: is the distance from the manufacturer to the project location, calculated

using the distance between the two zip codes (using Google maps).

The output of Equation 11 remains as inventory values that should be transformed into

environmental impacts. To convert inventory values into environmental impact, these values

should be characterized.

4.2.1.5 Characterization

The characterization step is one of the steps in performing LCA. The purpose of the

characterization process is to convert lifecycle inventory into comparable impact indicators.

For example, characterization can provide the relative terrestrial toxicity between Lead,

Chromium and Zinc. To convert the inventory data into an impact indicator, characterization

previously described as Equation 1 should be performed.

Where:

• Adjusted inventory values: These were already calculated in Equation 11.

159

• Characterization factor: The values for characterization are illustrated in Table 43, which

were extracted from TRACI.

As may be seen from Table 43, inventory datum such as Nitrogen Dioxide contribute to

Acidification Potential, Eutrophication Potential, and Smog Formation respectively, by the

following values (7.00E-01 kg SO2 eq /kg substance), (2.91E-01 kg N eq /kg substance),

(1.68E+01 kg O3 eq /kg substance). The example shown below will demonstrate how to use

the characterization table (Table 43), using the combination truck (light duty truck),

previously illustrated in Table 40 as an example.

Table 40 indicates that a combination truck emits Nitrogen Oxide In the amount of

0.000532 kg/ton.km. If the vehicle travels a distance of 1 km, and the total weight transported

equals 1 ton, then the resulting inventory value from the Nitrogen Oxide is: 0.000532

kg/ton.km × 1 km × 1 ton = 0.000532 kg.

By using the characterization values in Table 43, this value should be multiplied by

7.00E-01 to convert to Acidification Potential, leading to a total value of 3.72E-04 kg SO2 eq,

and should be multiplied by a value of 2.91E-01 to convert to Eutrophication Potential,

resulting in a value of 1.55E-04 kg N eq. This process should be repeated for all inventories;

then the total impacts from all these inventories should be summed for each environmental

impact category produced by the light duty truck. In Table 44, the final environmental impact

calculation for the various types of trucks, using various fuel types coupled with a total

weight transported, equals 1 ton; the total distance traveled equals 1 km.

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Table 43. Characterization values used (TRACI)

Substance Name

Global

Warming

Air (kg

CO2 eq / kg

substance)

Acidification

Air (kg SO2

eq / kg

substance)

Eutrophication

Water (kg N eq

/ kg substance)

Ozone Depletion

Air (kg CFC-11

eq / kg

substance)

Smog Air

(kg O3 eq /

kg substance)

Ammonia 0.00E+00 1.88E+00 7.79E-01 0.00E+00 0.00E+00

Nitrogen Dioxide 0.00E+00 7.00E-01 2.91E-01 0.00E+00 1.68E+01

Nitrogen Oxides 0.00E+00 7.00E-01 2.91E-01 0.00E+00 2.48E+01

Nitrous Oxide 2.98E+02 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Methane 2.50E+01 0.00E+00 0.00E+00 0.00E+00 1.44E-02

Carbon Dioxide 1.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Carbon Monoxide 0.00E+00 0.00E+00 0.00E+00 0.00E+00 5.56E-02

Sulfur Dioxide 0.00E+00 1.00E+00 0.00E+00 0.00E+00 0.00E+00

PM10 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

PM2.5 0.00E+00 0.00E+00 0.00E+00 0.00E+00 0.00E+00

Sulfur Oxides (SOx) 0.00E+00 1.00E+00 0.00E+00 0.00E+00 0.00E+00

VOCs 0.00E+00 0.00E+00 0.00E+00 0.00E+00 3.60E+00

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Table 44. Final transportation impact per vehicle and fuel type (1 ton and 1 km)

Truck/fuel type

Global Warming

Air (kg CO2 eq /

kg substance)

Acidification

Air (kg SO2 eq /

kg substance)

Eutrophication

Water (kg N eq /

kg substance)

Ozone

Depletion Air

(kg CFC-11 eq /

kg substance)

Smog Air

(kg O3 eq /

kg substance)

Fossil fuel

depletion

(MJ/ kg

substance)

Light duty/diesel 7.99E-02 3.90E-04 1.55E-04 0.00E+00 1.33E-02 2.00E-02

Medium duty/diesel 1.71E-01 2.63E-05 3.55E-04 0.00E+00 3.06E-02 4.28E-02

Heavy duty/diesel 3.24E-01 1.34E-03 5.55E-04 0.00E+00 4.62E-02 8.09E-02

Light duty/gasoline 6.20E-02 2.68E-04 9.84E-05 0.00E+00 8.65E-03 1.55E-02

Medium duty/gasoline 1.33E-01 5.74E-04 2.26E-04 0.00E+00 2.00E-02 3.32E-02

Heavy duty/gasoline 3.16E-01 8.35E-04 3.47E-04 0.00E+00 3.02E-02 7.89E-02

162

4.2.1.6 Total transportation impact

The total transportation impact is accomplished for all states in the EPD database

as simply the output of Equation 11, which is the environmental impact from the

manufacturer to the project location. However, the situation differs for the State of

Louisiana, since the values of EPD for transportation from the raw material extraction to

the manufacturing phase were provided separately by Athena Institute. Therefore, the

total transportation impact is the sum of the transportation impacts of two stages: from

the raw material extraction to the manufacturing (provided by Athena) and from the

manufacturer to the project location. The sum of both transportation modules is

illustrated in Equation 12.

(12)

Where:

• The transportation impact from the raw material extraction to manufacturing was

provided by Athena Institute separately. However, the impacts are given per 1 yd 3 for

each mix design, which means these values should be adjusted by multiplying each

impact by total concrete volume (Lv), as calculated earlier.

• The transportation impact from the manufacturer to the project location was

previously calculated (Equation 11) and characterized.

As an example, the total GWP for a certain mix design for the transportation impact

from the manufacturer to project location = (GWP from EPD) × (Total volume) + GWP

previously calculated and characterized in Equation 11, etc... The same concept applies

to other environmental impact values. After getting the total environmental impact of

transportation, the values should then be normalized and weighted as previously

described.

163

4.2.1.7 Overall environmental impact

After adjusting the environmental data coming from EPD, as well as the data coming

from the transportation module, both data should be added together per alternative, to obtain

one final environmental score for each alternative. This can be accomplished through

Equation 13

(13)

Where:

• The total transportation impact from the transportation module is the one previously

calculated in Equation 11. In addition, the transportation impact for the State of Louisiana

differs from all other states, since the transportation impact from the raw material

extraction to the manufacturing was provided separately; this value should be normalized

and weighted.

Finally, to obtain one single, relative, and comparable environmental score for each

alternative, the overall environmental score for each alternative is divided by the total

environmental score, or by all other alternatives. The result should be a unitless score, as

illustrated in Equation 14

Score for environmental impact alternative i=

(14)

The total environmental score is defined as the sum of the GWP, ODP, EP, AP, POCP, NRE,

followed by deduction of the value of the RE, which leads to GWP+ODP+EP+POCP+NRE-

RE. When the score rises, this means a higher environmental impact (emissions), and when

the score lowers, this means the alternative has a lower environmental impact as a better

alternative. In the event the user is assigned a weight for the environmental score, the

environmental score for alternative i becomes

164

(15)

4.2.2 MODULE 2: ECONOMIC PERFORMANCE

At that point, the design alternatives are evaluated for cost analysis. The cost analysis uses

the net present value for evaluating different design alternatives. This includes factors such as

initial cost (or current costs), and maintenance and rehabilitation costs (future costs). As

previously discussed, the economic analysis has values at the present and values in the future.

For this reason, the values should be compared at the same point in time. This will be

performed using the net present value. The equation used to obtain the net present value,

using current costs and future costs, was previously illustrated as Equation 4.

Where:

i = discount rate, n = year of expenditure, = present value factor

Alternatively, in case the future value is to be expected, this will lead to

Future value = Present value (1+i) n; where present value is the cost at current year, and the

future value is the expected amount in the future.

The final economic score that should be assigned to each alternative can be calculated

using Equation 16 (Lippiatt, 2007), where the net present value for the intended alternative is

divided by the sum of the net present value for all other alternatives. The output of this

equation should be a relative single score to compare between various alternatives.

Score for Economic impact alternative i = (16)

Where:

• NPVi: This is the net present value for the alternative required. This should have been

calculated previously by Equation 4.

• The NPVa: This is the net present value for all alternatives to be evaluated.

165

Moreover, in the event the user has assigned a weight for the economic impact (EconW),

the final equation thus becomes:

(17)

Where:

• EconW is the economic score assigned by the user.

• Score for economic impact, which was previously calculated using Equation 16.

4.2.3 THE OVERALL/ TOTAL PERFORMANCE

The final scoring criteria is simplified in Figure 31. The environmental performance

score includes GWP, ODP, AP, EP, renewable energy consumption, and non renewable

energy consumption. The economic scoring criteria includes initial cost (costs occurring at

the present and maintenance and rehabilitation items (occurring in the future).

Therefore, after all the previous calculations, the final sustainability score for the

environmental (module 1) and economic impact (module 2) is illustrated in Equation 18.

Overall final sustainability score = Weighted economic score per alternative + Weighted

environmental score per alternative (18)

166

Figure 31. Final scoring criteria

167

Figure 32. Environmental impact module

168

Figure 33. Economic impact module

169

products in order to evaluate whether the products are above or below average. The

benchmarking criteria can occur with respect to various criteria, such as benchmarking with

respect to a certain district/region/location/mix design breakdown, etc. The benchmarking

flowchart is illustrated in Figure 34, and the benchmarking equation is illustrated in Equation

19.

Figure 34. Benchmarking criteria flowchart diagram

Benchmarking = (19)

The benchmarking can occur with respect to various criteria, such as:

• A specific mix design breakdown, as for example, mix designs with a cement content of

400 lb.

• A specific location such as a district, in the case of the State of Louisiana, i.e., at a State

or National level.

BENCHMARKING MODULE

In addition to alternative design comparison, the sustainability data previously

collected (modules 1 and 2), may also be used to benchmark

170

In addition, the user has an option to select the mix designs that should be entered into

the benchmarking module. For example, if the user selected some benchmarking criteria

(such as geographic location, mix design breakdown, etc.) and the output is 10 mix designs,

the user still can select the mixes that need to be averaged from these 10 mixes. After user

selection the environmental impact, such as GWP values, are summed together and averaged

over the selected mixes, with the same procedure for AP values, etc. As for the cost items, the

entire cost of the mix designs is summed together as well, then divided by the number of

selected mixes. Once the average result is displayed, the user can then average/benchmark the

product.

All the equations previously described will hold, except for the fact that the

environmental impact, as well as the economic impacts, will be averaged across all selected

alternatives and finally treated as one single value. The equations previously described in the

alternative design module are illustrated in Table 45, and the differences are indicated to be

used in the benchmarking module.

Table 45. Benchmarking module equations

Equations/step previously used in the alternative design

comparison module

Application in the benchmarking

module

Assigning weights for economic and environmental

impacts

Yes, this equation still holds and

the sum of both weights should

sum to 100. No changes

Total layer volume calculation

LV = LT × LW × LT

Yes, still holds.

There is a slight change in this

equation. The impacts reported

from the EPD are averaged

impacts based on the selection

criteria by stakeholder and no

longer individual impacts. For

example, if the filtering criteria

narrowed down to 10 options,

the impacts from EPD

corresponding to these options

are averaged.

Table 45 (cont.)

171

Equations/step previously used in the alternative design

comparison module

Application in the benchmarking

module

MOR (psi) = 2.3 fc 2/3 Yes, still holds. This is no

affected by the benchmarking

module

Weighted impact = assigned weights × normalized

value

Yes, still holds. All the assigned

weights are still the same: BEES,

the EPA, the default value for the

software and the custom weights.

The normalized value is the

average environmental impact

Weight for concrete transported

M = D × Lv

There is a slight change in this

equation. The weight of the

concrete transported is the

average value for the selected

mixes. There are no individual

values anymore.

Adjusted inventory values = 2× Emissions of each

truck (kg/(ton.km))×total weight transported (truck

weight (ton)+weight of concrete transported (ton)×total

distance (km)×number of trucks

There is a slight modification in

this equation as well. The total

weight of concrete transported

should be an averaged value. The

average distance is calculated as

well and not individual ones.

Impact category = adjusted inventory values ×

characterization factor

There is a slight change in this

equation. The inventory values

are averaged inventory values

and not individual ones.

Total number of loads = total weight concrete

designed/ truck carrying capacity

The average number of trucks for

the selected alternatives is used

and not the individual ones.

There is a slight change in the

equation. The transportation

impact are the average

transportation distances and not

individual ones.

Total environmental impact = total environmental

impact from the transportation module + the

environmental impact resulting from concrete layer

design

There is a slight change. The

environmental impact is the

average value and the

environmental impacts from

concrete are average values as

well

Score for environmental impact alternative i=

This equation does not hold

anymore, since alternatives are

no longer compared.

Table 45 (cont.)

172

Equations/step previously used in the alternative design

comparison module

Application in the benchmarking

module

Weighted Environmental score per alternative

There is a slight change. The

environmental impact for

alternative i is no longer valid,

since the values are now

averaged.

Yes, this equation still holds to

perform a lifecycle cost analysis.

However, the values used are the

average values for the selected

mix designs

There is a slight change. The

economic impact for alternative i

is no longer valid, since the

values are now averaged.

Overall sustainability score per alternative

The overall sustainability score is

still the sum of the

environmental and economic

score for the average values and

not individual values anymore

4.2.3.1 THE DEVELOPMENT OF A TOOL FOR DATA MANIPULATION

ENGINEERING EQUATIONS

A software was developed to use all the previous described data. Therefore, the objective of

this section is to describe how to use and integrate the previous data into the newly developed

software1. Equations, as well as screenshots from the program, are provided for the user. The

algorithm used in the software is also provided. This software, as a tool for the previously

used data, will therefore utilize the same background for performing calculations. The

software allows an analysis of multiple designs and layers. The software workflow is

illustrated in Figure 35. The workflow is as follows:

• Input values: These are mostly related to project and design information, such as zip code,

layer thickness, and discount rate for the economic analysis.

1 Software credit should be given to Qinadong Nie, LSU graduate student, computer science

department.

173

• Databases: 1) EPD database: contains environmental impacts and inventory matrix; 2)

cost analysis database

• Documents: This section contains the product category rule (PCR) associated with the

EPDs used in the program.

• The Output: The output provides information about the environmental impact/inventory

values of each mix design, as well as the transportation stage. Also, the output displays

economic analysis information for the design. The software also allows alternative design

comparison and benchmarking by using the same equations previously illustrated.

Figure 35. Software workflow

4.3 SOFTWARE DEMONSTRATION

There are five different tabs in the following order: layer information, weight tab,

transportation tab, economic analysis tab, and summary/report tab.

1. Layer information tab: This tab enables the selection of analysis purpose (product design

alternative vs. benchmarking), design type (new pavement), and pavement type (rigid).

The user should input the layer thickness. The unit of measurement is given in both U.S.

units (inch) and S.I. units (meters). The project zip code is a user input as well. The layer

information tab is illustrated in Figure 36.

174

Figure 36. Layer information tab

2. Once the layer information is identified, corresponding materials are loaded from the

database. As previously discussed, material selection criteria are inclusive of the:

compressive strength value, geographic region and mix design description such as cement

(lb), fly ash, coarse aggregates, and fine aggregates, etc. This is illustrated in Figure 37.

3. The selection criteria for the State of Louisiana are different. These were specifically

designed to match the mix designs used by the Louisiana Department of Transportation

districts. The criteria include: a) cement (lb), b) fly ash (lb), c) slag (lb), d) fine aggregates

(lb), e) coarse aggregate 1 (lb), f) coarse aggregate 2 (lb), g) water (gallons), h) water

reducer (oz), i) air (%), j) air entertainer (oz), k) set accelerator (oz), l) super plasticizer

(oz), m) special additive A (oz), n) special additive B (oz), and o) special additive C (oz).

This particular layout is illustrated in Figure 38

175

Figure 37. Selection/filtering process

Figure 38. Selection criteria for the State of Louisiana

176

Once the user saves the selected options, the button turns into green, indicating that the

options were saved, as illustrated in Figure 39.

Figure 39. Saving process

4. Weights tab: This tab assigns weights for the environmental and economic impacts. The

sum of both weights should equal 100. In addition, this tab assigns different weights for

various environmental impacts/inventory matrix (GWP, ODP, AP, EP, POCP, and total

primary energy consumption (or non renewable energy consumption and renewable

energy consumption). As discussed earlier, various weights may be used, depending on

stakeholder preference. This includes the BEES weights, the EPA’s weights, etc.

Moreover, the software allows the user to input custom values. Also, in the event the user

did not input values, the software also has default values. All existing weights provided

by the software are illustrated in Table 46. The weight tab is illustrated in Figure 40 for

the default software value.

177

Table 46. Various weights used by the software

Weights Default

value

BEES

Stakeholder

Panel

EPA

Science

Advisory

Board based

Custom

weight

GWP 20% 45% 35% User input

ODP 15% 3% 10% User input

AP 15% 5% 11% User input

EP 15% 10% 10% User input

POCP 15% 5% 12% User input

NRE 10% 16% 11% User input

RE 10% 16% 11% User input

Total 100% 100% 100% 100%

Figure 40. Performance weight (environmental vs. economic)

5. Transportation tab: The transportation tab evaluates the environmental impact of

transportation. Two types of fuels can be assigned (diesel and gasoline), and three

categories of trucks are allowed (light duty truck, medium duty truck, and heavy duty

truck). The transportation distance from the manufacturer to the project location is

calculated as follows: The project location requires an input by the user; then the

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manufacturer/plant location zip for each mix design is located in the software. The

software then calculates the total distance between the two zip codes by connecting to

Google. The user should be connected to the internet when using the distance calculator.

As for the benchmarking module, the user can enter the manufacturer location. The

transportation tab is illustrated in Figure 41 for the light duty truck and gasoline fuel.

Figure 41. Transportation impact tab

6. Economic analysis tab: The economic analysis tab uses the net present value to evaluate

the economic impact of a design. The economic analysis tab is connected to the cost

analysis database described previously. Cost items are first selected by checking them as

illustrated in Figure 42.

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Figure 42. Economic analysis tab

Final cost analysis results for alternative design comparison module are illustrated in a

graph format as shown in Figure 43.

Figure 43. Economic analysis and alternative design comparison

Additionally, the summary/export tab provides the breakdown of the output in

terms of A1, A2, and A3 in regard to the environmental impact for the State of Louisiana,

as illustrated in Figure 44.

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As for the benchmarking module, the procedure is as follows. First, the user puts the

software into the benchmarking module, and inputs the number of designs and layer

thicknesses. Having selected the criteria, the user must benchmark with respect to the

filtering criteria; the resulting mixes are then averaged and the design will proceed, using the

averaged environmental impacts values. The user still can assign weights for environmental

and economic impacts, as well as weights for various environmental impacts. Screenshots

from the software are illustrated in Figure 45. The design will proceed normally as discussed

earlier, before using the average value.

Figure 44. Environmental performance breakdown display

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Figure 45. Benchmarking module

4.4 STUDY SIGNIFICANCE: THE BIGGER PICTURE. HOW CAN THIS

FRAMEWORK BE USED IN THE REAL WORLD?

This methodology/framework/tool will quantify the sustainability of pavement design, using

both an economic and environmental score. The application of this tool can be summarized

into three categories: Accounting, decision making, and process improvement (FHWA, 2015)

4.4.1 ACCOUNTING

Accounting is the process of measuring only for the goal of quantification. This process is

used in case of reporting emissions, such as GHG reporting. In fact, there exists no current

rules for quantifying sustainability in the United States compared to Europe, where

quantification methods are more advanced and required by various entities (FHWA, 2015).

In the United States, this tool would be most useful in mandates requiring

quantifications of emissions, such as greenhouse gases. This measurement can be either on

the State level or the National level (which the tool can currently handle, since it contains

EPDs for other states). Some of the mandates associated with GHG emissions are as follows::

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• The National Environmental Policy Act: This policy proposes that in the event there is a

project emitting a huge amount of greenhouse gases (27500 tons or more of CO2),

stakeholders should perform a quantitative and qualitative analysis for these emissions

(Sutley, 2010).

• Quantifying emissions for states mandates. Currently there is a minimum of thirty states

that have issued GHG mandates (Center for Climate and Energy Solutions, 2012), which

will require the assessment and quantification of GHG.

(FHWA, 2015)

4.4.2 CAP AND TRADE LEGISLATION

The government mandated a certain limit for industry’s greenhouse gas emissions,

which was known as the cap and trade policy. This policy was mandated to decrease

pollution. Should the cap limit be exceeded, the industry must pay a penalty. This cap and

trade legislation was passed in June 2009. The target of this registration is to decrease GHG

by 3% in 2012, 20% by 2020, 42% by 2030 and 83% by 2050 (FHWA, 2015)

In a further analysis of past cap and trade legislation, a successful example may be

noted for the reduction of Sulfur Dioxide, known as the Acid Rain Program, under Title IV of

the 1990 Clean Air Act (CAA) Amendments. In 1995, the United States EPA become aware

of high levels of acid rain in the Midwest and Northeast region; mostly resulting from coal

burning plants. These plants emitted a significant amount of Sulfur Dioxide. The government

then put a cap and every plant was held responsible for lowering their emissions to match the

cap limit. The government then issued credits for the plants equal to one ton of emissions of

Sulfur Dioxide (EPA, 2017). At the end of each year, plants had to report the number of

credits used and whether the plants had sufficient credits. Plants under the cap could save the

credits or emissions for future use, or sell it to other plants (EPA, 2017).

183

4.4.3 DECISION MAKING

Decision making is defined as measurement performed to assess the qualities and

quantities that can help decision making in organizational or project levels (FHWA, 2015).

Various alternatives can then be compared for the purpose of improvement. In some states,

decision making tools are required (such as LCCA) and will be more required in the future

(Senate and House of Representatives, 2012).

4.4.4 PROCESS IMPROVEMENT

The FHWA defined process improvement as” … the measurements that provide feedback

data to support the refining process and updating the overall methodology.” These

measurements can then be compared to benchmarking or any other reference criteria to

produce better results.

4.4.5 HOW DOES THE TOOL FIT?

By further analysis into the developed framework/tool, the tool can work for accounting as

well as for laws and mandates requiring quantifications of emissions such as the cap and

trade legislation. Both modules can aid the accounting method. For example, the product

comparison module can help quantify the total emissions for concrete per total design

volume, and to evaluate the impact of this specific design and whether the design exceeds the

limits.

Moreover, the benchmarking module can help the user by measuring the impact of his

product with respect to the market average. By comparison, the user can then lower his

emissions, in case the emissions exceed the average limit. Also, the developed tool can help

in the decision making process improvement processes. The product comparison module can

help evaluate the environmental impact of the product as well as the economic impact,

therefore, enabling the stakeholder to decide which alternative has higher/lower

environmental score compared to the other.

184

For the process improvement, the benchmarking module allows the stakeholder to

benchmark his product with respect to similar products (such as similar compressive strength

value, mix design breakdown, or geographic location) to find whether the environmental

impact of the product is below or above the average. In case it is above average, this means

more process improvement should be performed in order to achieve a similar environmental

impact.

4.5 SUMMARY

• This chapter presented methodology for the newly developed framework. Modification of

the data provides a guarantee of equivalence and comparability.

• For the environmental module, the data from the transportation module, adjusted with

data from the EPD, allowed both to be added together.

• For the cost analysis database, the initial cost as well as the maintenance and

rehabilitation cost were first adjusted by using the net present value to ensure that tje two

costs are comparable; then the costs were added together.

4.6 REFERENCES

Caltrans. (2017). Weight Limitation. Retrieved from

http://www.dot.ca.gov/trafficops/trucks/weight.html

EPA (2006). LIFE CYCLE ASSESSMENT: PRINCIPLES AND PRACTICE. Retrieved

November 3, 2016, from http://www.cs.ucsb.edu/~chong/290N-

W10/EPAonLCA2006.pdf

EPA 2017. Acid rain Program. Retrieved from

https://www.brookings.edu/blog/planetpolicy/2015/10/21/the-return-of-cap-and-trade-

is-good-news-for-u-s-climate-policy/

Lifecycle Assessment of Automobile/Fuel options (2016), Mellon University, Pittsburgh,

www.cmu.edu/gdi/docs/lca-of-automobile.pdf.

Learn About Sustainability. (2016). Retrieved April 17, 2016, from

https://www.epa.gov/sustainability/learn-about-sustainability#what

Lippiatt , B. (2007). Building for Environmental and Economic Sustainability Technical

Manual and User Guide. Retrieved December 1, 2016, from

http://ws680.nist.gov/publication/get_pdf.cfm?pub_id=860108

185

Naik, T. (2008). Sustainability of concrete construction. Retrieved April 17, 2016, from

http://courses.washington.edu/cee380/NAIKconcrete-sust.pdf

Stranddorf, H., Hoffmann, L., Schmidt, A., & Technology, F. (2005). Impact categories,

normalization and weighting in LCA. Retrieved from

http://www2.mst.dk/Udgiv/publications/2005/87-7614-574-3/pdf/87-7614-575-1.pdf

Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-

Duty Vehicles (2010). Retrieved 2017, from

https://www.nap.edu/read/12845/chapter/4

The Mechanistic Empirical Pavement design. Retrieved from

https://www.fhwa.dot.gov/engineering/geotech/pubs/05037/images/f173.gif

Walls., & Smith. (1998). Pavement interactive. Retrieved from

http://www.pavementinteractive.org/life-cycle-cost-analysis

What Is Mechanistic-Empirical Design? – The MEPDG and You. (2012). Retrieved June 1,

2016, from http://www.pavementinteractive.org/2012/10/02/what-is-mechanistic-

empirical-design-the-mepdg-and-you/

186

CHAPTER 5. DEMONSTRATION OF THE DEVELOPED FRAMEWORK IN CASE

STUDIES

5.1 INTRODUCTION

As previously discussed, the pavement ME design approach is considered a highly

temporary stage between the commonly used empirical design and the purely mechanistic

design. The pavement ME design includes inputs such as material properties, traffic and

climate. Climate has a powerful impact on the overall pavement performance. This is because

material properties change with climatic impacts, such as temperature and moisture

circumstances. The impact of climate can be seen in pavement distresses (Breakah et al.,

2011).

Through climatic analysis in National Centers regarding environmental information,

scientists have found nine climatically consistent regions in which to place current climate

anomalities in a historic perspective. Therefore, to account for various climatic conditions,

various case studies will be presented in different states. The following states will be

considered for evaluation: Texas and Louisiana. Each case study will have a custom

pavement design in regard to climate conditions and related data (EPD and cost data). In

addition, the cost analysis performed in the State of Texas is extracted from literature review

and is not part of the scope/cost analysis database of this study. However, for a complete

demonstration of the new framework, cost data should be used. These case studies are already

extant, which means these have satisfied the technical criteria.

5.2 CASE STUDIES IN TEXAS

The object of this study is to assess the use of ICC in the concrete pavement design in the

State of Texas (Rao & Darter, 2003). Internally cured concrete (ICC) is a mix design type in

which a percentage of coarse or fine aggregate is replaced with similarly sized, pre-wetted,

lightweight aggregate (LWA). An internal curing process is a means to provide hydrating

187

concrete with enough moisture from within the mixture, which would serve to substitute

water loss due to chemical shrinkage (Rao & Darter, 2003).

ICC has been used in several states, in applications such as bridge decks, toward

decreasing the amount of plastic shrinkage, cracking, and other random cracks. ICC has also

proven to have good constructability and excellent performance in many states, such as New

York, Virginia, Utah, North Carolina, Georgia, and Ohio (Rao & Darter, 2003). ICC might

display significant sustainability and durability benefits, such as longer life. Currently, there

are many states interested in longer life pavement.

For example, some states have “long life pavement” programs. These long life

pavements have design lives of 20, 30, 40, 50, and 60 years (Rao & Darter, 2003). States

such as California have even reached a design life of 100 years, which has a great advantage

over the environment and government of longer life pavement (Rao & Darter, 2003). When

comparing the life of many concrete types with or without internal curing, such as

conventional concrete and high performance concrete bridge decks, results demonstrated that

service life tends to be 22 years for conventional concrete, 40 years for high performance

concrete without internal curing, and 63 years for high performance curing.

The Pavement ME was used to evaluate the performance of the ICC; the developed

tool was applied to evaluate associated environmental and economic impacts. Notably, the

cost analysis was collected from project/literature review, because cost data does not exist in

the database for states other than Louisiana. However, this example will be used as an

illustration on how to use the framework/developed tool for states other than Louisiana.

5.2.1 PROJECT DESCRIPTION

The selected project is located in SH 121, west of I-75 and east of the Dallas North

Tollway, falling in the Dallas Fort Worth weather station (Rao & Darter, 2003). The

pavement is expected to serve moderate traffic volume with an average annual daily traffic

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(AADT) of 23,400 and a linear traffic growth of 4%. The design analysis period was assumed

to be 30 years for a CRCP design. The initial IRI limit is 63, together with a terminal IRI of

160 with a reliability level of 90%. The terminal thresholds for transverse cracking,

longitudinal cracking, and corner cracking represented 10% of the slabs cracked (Rao &

Darter, 2003). The project has a zip code of 75424.

5.2.2 INITIAL AND ALTERNATIVE DESIGNS

Details of the design and layers properties are illustrated in Table 47 for

reproducibility. The original vs. the alternative trial designs are illustrated in Figure 46. Both

alternatives have the same design and layers, with the exception of the top layer. The

alternative design has a thinner concrete thickness, consisting of internally cured concrete

(ICC).

Table 47. Design details and layers properties

Criteria Conventional concrete

design 1

Internally cured

concrete

design 2

Shoulder type Tied PCC Tied PCC

Steel content,

percent 0.7 0.7

Bar diameter,

inch 0.75 0.75

Steel depth, inch 6 6

Base/ slab

friction 7.5 7.5

Compressive

strength value

(psi)

5200

6000

5.2.3 MATERIALS PROPERTIES AND LAYER DESIGN

The concrete mix designs used in this analysis were 6000 psi for ICC and 5200 psi for

conventional concrete. The 5200 psi was extrapolated to 5500 psi to match the value in

EPD’s database, and the 6000 psi was used as listed.

189

11” CRCP 10” CRCP

(conventional

concrete) (ICC)

4 inch HMA,

good quality

base

4 inch HMA,

good quality

base

6.0” Aggregate

Subbase

6.0”

Aggregate

Subbase

10’’ lime 10’’ lime

Subgrade Subgrade

(a) (b)

Figure 46. (a) Initial design vs. (b) Alternative design

5.2.4 ENVIRONMENTAL PERFORMANCE

To assess the environmental performance, the new framework developed in this study will

evaluate the environmental impact of this project. The developed framework will be used,

and the solution provided in detail for replication as follows:

1. Select the state you want to evaluate mix designs: The state is Texas.

2. The purpose of the design is to provide an alternative design comparison. The stakeholder

is interested in evaluating the environmental impact of various alternatives. These various

alternatives are presented as various mixes for each design.

3. Select the number of designs to evaluate: two designs (ICC vs. conventional concrete).

4. Select the number of mixes to evaluate: 3 PCC mix designs for both alternatives, if

possible.

5. Assign weights for the environmental and economic impacts. Both impacts will be

assigned a weight of 0.5.

6. In this example, there is no need to convert modulus of rupture to compressive strength

value, since the compressive strength value is already given.

7. Select alternative mixes from the EPD data to evaluate the environmental impact. The

user enters a specific mix design: to look for an environmental impact and/or look for the

compressive strength value

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By further considering the available compressive strength in the database for the State of

Texas, there is no compressive strength value of 5200 or 5500 psi. Therefore, this value will

be rounded out to 6000 psi for both designs. Table 48 summarizes the compressive strength

value, as well as the mix design breakdown required by the user.

Table 48. Mix design breakdown required and compressive strength value

Compressive

strength

value (psi)

Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Mixing

water

(lb)

Air

%

6000 500 130 1200 1700 230 1

This exact mix design breakdown is not in the database and therefore, the nearest mix

design breakdown will be used. Available mix designs for the compressive strength value of

6000 psi are illustrated in Table 49. The nearest mix design for the one required by the user is

mix design number 4, when comparing the amount of cement. Therefore, this mix design will

be selected.

There are not many mix designs from which to select, since a limited number of

companies have published their EPDs to date. This will be discussed later in the study

limitations and future work. The user intended to select three mix designs to evaluate.

However, due to data limitation, only one mix design is available. The other option is to

select the mix design with a cement content of 564 lb. Nevertheless, this mix design will

show a higher environmental impact and is more expensive than the mix design required by

the user. The next step is to find the nearest manufacturer selling the selected mix design. The

following manufacturers sell this product (same product, but different locations). Four

manufacturers in four different locations sell this product, accounting for a total of 4×4 = 16

locations/manufacturers.

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The project zip code is 75424. The total distance between each zip code and the

project zip code is illustrated in Table 50. In this case, the nearest manufacturer to the project

location is manufacturer 9, with a total transportation distance of 30.3 miles. The

manufacturer zip code exists in the database.

The environmental impact of mix 4 is illustrated in Table 51. The environmental

impact varies by each manufacturer, since each one uses a different technology. Both

alternatives, produced by different manufacturers, will be evaluated, since not many products

exist in the database. These are the values extracted from EPD, with no modifications. As

illustrated, the values are given per 1 yd3. The sum of the impacts for A1 are: raw material,

for A2: transportation from raw material extraction to manufacturing, and for A3:

manufacturing stage. These values are given as a sum; no breakdown is given for each phase.

These values are given per 1 yd3; some adjustments need to be performed to adjust the

environmental impacts per the total design volume. The unit conversions for use in this case

study are illustrated in Table 52. The table converts all other units to units of yd.

Accordingly, the final volume for each design is illustrated in Table 53. The calculation was

performed using Equation 6:

Finally, the total environmental impact for the design should be adjusted according to

the overall design volume, using Equation 7.

(7)

For example, the total adjusted GWP, for design 1 =

The volume 2151.09 yd3 × 353.238 kg CO2 eq/yd3=759849.427kg CO2 eq

The environmental impact will be adjusted accordingly for each alternative. Final results are

indicated in Table 54.

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Table 49. Available mix design breakdown for the State of Texas

Mix

number Cement weight

(lb)

Water cement

ratio

Mixing water

(lb)

Fly ash weight

(lb)

Slag weight

(lb)

Fine aggregate

(lb)

Coarse aggregate

(lb)

1 322 0.36 240 336 0 1256 1900

2 564 0.35 250 141 0 1285 1840

3 635 0.31 260 212 0 1256 1750

4 526 0.42 275 132 0 1200 1900

Table 50. Total distance

Number Project

zip code

Manufacturer’s zip code Total distance

(mile)

1 75424 75212 58

2 75424 75038 56

3 75424 76106 79

4 75424 75081 39.9

5 75424 75035 30.8

6 75424 75019 49

7 75424 75067 48.5

8 75424 76118 72.3

9 75424 75078 30.3

10 75424 76134 85

11 75424 76247 79.5

12 75424 75165 85

13 75424 75160 44.1

14 75424 76092 66

15 75424 76177 73

16 75424 76179 78

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Table 51. Environmental impact extracted from EPD (A1, A2, and A3)

Mix

design

GWP

kg CO2

eq/yd3

ODP

kg CFC-11

eq/yd3

AP

kg SO2

eq/yd3

EP

kg N

eq/yd3

POCP

kg O3

eq/yd3

NRE

MJ/yd3

RE

MJ/yd3

1 353.238 3.99E-06 1.935 0.0550 27.142 1865.586 13.984

2 352.473 3.98E-06 1.924 0.0542 26.836 1851.823 13.961

Table 52. Conversion table to yards

Original unit Factor to convert to yd

1 inch 1/36

1 foot 0.33

1 mile 1760.006

Table 53. Final layer volume

Dimension Design 1 Design 2

Layer thickness (inch) 11 10

Length (mile) 1 1

Width (feet) 12 12

Total volume (yd3) 2151.09 1955.54

Table 54. Adjusted environmental impact per volume for each design

Design GWP

kg CO2

eq

ODP

kg CFC-

11 eq

AP

kg SO2

eq

EP

kg N eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

1 759849.42 0.009 4162.72 118.41 58386.69 4013057.58 30081.48

1B 758204.73 0.009 4139.69 116.77 57728.82 3983453.05 30032.14

2 690772.20 0.008 3784.29 107.65 53078.81 3648234.16 27346.80

2B 689277.02 0.008 3763.36 106.15 52480.74 3621320.96 27301.94

As illustrated, the values have different units. Therefore, they should be normalized to

be consistent and unitless, to be summed altogether later. The normalization values used are

illustrated in Table 55.

Table 55. Normalization values used

GWP (kg CO2 eq/ yd3) 24000

ODP (kg CFC-11 eq/yd3) 0.160

AP (kg SO2 eq/yd3) 91

EP (kg N eq/yd3) 22

POCP (kg O3 eq/yd3) 1400

NRE (MJ/yd3) 288572.509

RE (MJ/yd3) 24874.54785

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The normalization can be performed by dividing the environmental impact per the

normalization value. This may be accomplished by following Equation 2.

For example, the normalization value for the GWP for design 1 =

759849.427 kg CO2 eq/24000 kg CO2 eq = 31.660. Final results are illustrated in Table 56

Table 56. Normalized value for adjusted environmental impact per total volume

Alternative GWP ODP AP EP POCP NRE RE

1 31.660 0.054 45.744 5.383 41.705 13.907 1.209

1B 31.592 0.053 45.491 5.308 41.235 13.804 1.207

2 28.782 0.049 41.586 4.893 37.913 12.642 1.099

2B 28.720 0.049 41.356 4.825 37.486 12.549 1.098

5.2.5 TRANSPORTATION MODULE

The two parts of the transportation module are as follows: a) Part 1: Transportation from the

raw material extraction to the manufacturing phase. This does not exist for states other than

Louisiana; b) Part 2: Transportation impact from the raw material extraction to the project

location. In order to calculate the transportation impact from the raw material extraction to

the project location, the distance between the manufacturer to the project location first should

be determined. This can be accomplished by calculating the distance between the two zip

codes of the project location, as well as the manufacturer’s location. The zip code of the

project location is 75424, while the manufacturer zip codes are presented in the EPD for each

mix design. Table 57 illustrates the project zip code, the manufacturer zip code, the distance

between the project, and the manufacturer’s location (calculated through Google maps).

Table 57. Total transportation distance (manufacturer to project location)

Design Project

location

Manufacturer

location

Total distance

(miles)

Total distance

(km)

1 75424 75035 30.8 49.280

1B 75424 75035 30.8 49.280

2 75424 75078 30.3 48.480

2B 75424 75078 30.3 48.480

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Moreover, the type of truck used to transport concrete is a heavy duty truck (80,000

lbs or 36.28 tons), and diesel fuel. The total weight of concrete to be transported is illustrated

in Table 58. To obtain the total weight of the concrete to be transported, Equation 9 should be

used. This can be accomplished through the use of Equation 9:

Where: M is the total mass to be transported, D is mix design density (in the database

as collected by the manufacturer, with Lv as the total design volume, based on corresponding

dimensions). For example, the density for design 1 = 4033 lb/yd3 and the total design volume

= 2151.09 yd3; therefore, the total design weight = 4033 lb/yd3×2151.09 yd3 =8675376.396

lb. This weight value then should be converted to metric ton, which will be accomplished by

multiplying the value by 0.00045359.

This is to ensure the units are consistent, since the transportation equation will be

used. The total weight is the weight of concrete transported + weight of truck = 8675376.396

lb + 80000 lb = 8755376.4 lb. Total weight conversion to ton = 8755376.4 lb × 0.00045359 =

3971.35 ton. Final values are illustrated in Table 58.

To get the total number of loads required, Equation 10 should be applied:

For example, for design 1 = 8675376.39/54000 = 160.65 loads.

Values are illustrated in Table 58 as seen below:

Table 58. Weight of concrete to transport

Design Density

(lb/yd3)

Total weight per design

volume of concrete

(lb)

Total

number of

loads

Total weight

(truck+ concrete)

(ton)

1 4033 8675376.39 160.65 3971.35

1B 4033 8675376.39 160.65 3971.35

2 4033 7886705.81 146.05 3613.61

2B 4033 7886705.81 146.05 3613.61

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To adjust the inventory values coming from the transportation module, Equation 11

should be used:

× total number of loads

The emissions/ inventory for the heavy duty truck is illustrated in Table 59.

Table 59. Heavy duty truck emissions

GWP

kg CO2 eq

ODP

kg CFC-11 eq

AP

kg SO2 eq

EP

kg N eq

POCP

kg O3 eq

NRE

MJ

3.24E-01 0.00E+00 1.34E-03 5.55E-04 4.62E-02 8.09E-02

For example, to calculate the transportation impact from the manufacturing to the

project location for GWP for Design 1, the Adjusted inventory values = 2 × 3.24E-01 kg

CO2/ton.km 3971.35118ton × 49.280 km ×160.655 loads =20374106.14 kg CO2 eq. All

values are illustrated in Table 60.

5.2.6 TOTAL ENVIRONMENTAL IMPACT

The total environmental impact consists of the total environmental impact coming from

concrete design (EPD) as well as the total transportation impact. This will result for the

values given in Table 61. For example, the environmental impact extracted from EPD and as

adjusted based on design volume, was previously described. An example is provided for

Design 1 and Alternative 1. Environmental impact from EPD (adjusted per volume) + total

transportation impact =759849.42 kg CO2 eq + 20374106.14 kg CO2 eq =21133955.57 kg

CO2 eq

Table 60. Transportation impact from the manufacturer to project location

Alternative GWP

kg CO2

eq

ODP

kg CFC-

11 eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

1 20374106.14 0.00 84263.27 34900.08 2905196.61 5087238.23 0.00

1B 20043357.66 0.00 82895.36 34333.52 2858034.33 5004653.19 0.00

2 16853489.63 0.00 69702.70 28869.40 2403182.78 4208170.71 0.00

2B 16579894.02 0.00 68571.16 28400.74 2364170.07 4139856.25 0.00

197

Table 61. Total environmental impact per alternative

Alternative

GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

1 21133955.57 0.009 88426.00 35018.50 2963583.31 9100295.81 30081.48

1B 20801562.39 0.009 87035.06 34450.30 2915763.15 8988106.25 30032.14

2 17544261.84 0.008 73486.99 28977.05 2456261.59 7856404.87 27346.80

2B 17269171.05 0.008 72334.53 28506.90 2416650.81 7761177.21 27301.94

These total environmental impacts must be normalized. Values after normalization are

illustrated in Table 62 for each alternative.

Table 62. Normalized values for total environmental impact

Alternative GWP ODP AP EP POCP NRE RE

1 880.58 0.054 971.71 1591.75 2116.84 31.53 1.20

1B 866.73 0.053 956.42 1565.92 2082.68 31.14 1.20

2 731.01 0.049 807.54 1317.13 1754.47 27.22 1.09

2B 719.54 0.049 794.88 1295.76 1726.17 26.89 1.09

5.2.7 WEIGHTING THE ENVIRONMENTAL IMPACT

Based on stakeholder preference, weighting can be assigned to the impacts. The weighting

procedure will be used here for demonstration. Default weights were used for this case. The

weights are illustrated in Table 63.

Table 63. Weights used in the study

GWP ODP AP EP POCP NRE RE Total

0.200 0.150 0.150 0.150 0.150 0.100 0.100 1

The total environmental impact after the weighting process is illustrated in Table 64.

Equation 3 can be used to convert the environmental impacts into weighted environmental

impacts: For example, for Design 1, the weighted value = 880.58× 0.200 = 176.116

The total environmental score is the sum of all the environmental values together and then the

RE value is deducted: Total environmental score = GWP+ODP+AP+POCP+NRE-RE

For example, for Design 1, the total environmental score =

198

176.11+0.008+145.75+238.76+317.52+3.15-0.12=881.20

The relative score is the environmental impact score compared for each alternative,

with respect to the other alternatives. This can be accomplished through Equation 14.

Score for environmental impact for each alternative =

Total environmental score for alternative i/ ∑Environmental impact for all alternatives

For example, in the score for Design 1, there are two alternatives (or mix designs). This will

lead to the following equation: = 881.20/ (881.20+867.10+730.69+719.02) = 0.276

This equation was repeated for all other alternatives. Values are illustrated in Table

64. In this case, the alternative having the lowest score is the one that has the lowest

environmental impact. In this case, alternative 1B for Design 1 is the best alternative, as is

alternative 2B for Design 2.

Should the stakeholder assign a weight for the environmental score (which is

presented in this study, since the assigned weight is 0.5), the final environmental score after

adjusting per the weight can be calculated, using Equation 15.

Weighted environmental score per alternative = EnvW × score for environmental

impact for the alternative. For example, for Design 1 and Alternative 1, the weighted score =

0.5 × 0.272=0.138. In the instance of Design 2, the overall layer thickness for Design 2 is

lower than Design 1. Final weights are illustrated in Table 65

Table 64. Total environmental impact after normalizing and weighting

Alternative GWP ODP AP EP POCP NRE RE Total

1 176.11 0.008 145.75 238.76 317.52 3.15 0.12 881.20

1B 173.34 0.008 143.46 234.88 312.40 3.11 0.12 867.10

2 146.20 0.007 121.13 197.57 263.17 2.72 0.11 730.69

2B 143.91 0.007 119.23 194.36 258.92 2.69 0.11 719.02

199

Table 65. Relative score and environmental score

Alternative Total Relative

score

Assigning

environmental

score

1 881.201 0.276 0.138

1B 867.101 0.271 0.136

2 730.692 0.228 0.114

2B 719.023 0.225 0.112

5.2.8 ECONOMIC IMPACT

As previously described, the economic analysis will be performed by performing a lifecycle

cost analysis for each alternative. This lifecycle cost analysis consists of the initial cost

(occurring at present), and the maintenance and rehabilitation cost (occurring in the future).

Notably, the cost database in this study contains no cost analysis for the State of Texas. The

cost information was collected from the actual project in Texas. However, the initial cost for

each mix design exists in the database, and was used in the study.

The initial cost for the selected mix designs is extracted from the database. Both

alternatives have the same price, except that the internally cured concrete is $10/yd3 more

expensive than the conventional concrete. Values are illustrated in Table 66. To get the total

costs adjusted per volume, the initial cost is multiplied by the total design volume. For

example, for Design 1, the material cost is given in 1yd3, which means the cost should be

adjusted to account for the total design volume. Total cost = 213 ($/yd3) ×2151.09 yd3 =

$458183.77. The initial cost items were previously collected at the current year (2017), so

there exists no need to discount the values or to use the net present value equation.

Table 66. Initial material price for each alternative

Design

Initial

material

cost

($/yd3)

Design

volume

(yd3)

Total initial

cost adjusted

per volume

($)

1 213 2151.09 458183.77

1A 213 2151.09 458183.77

2 223 1955.54 436086.13

2B 223 1955.54 436086.13

200

As for the overall initial construction cost, the project assigns a percentage for

maintenance over time (5%), design cost (10%), and construction inspection services (10%).

The maintenance and rehabilitation items breakdown are illustrated in Table 67.

Table 67. Initial cost item overall

Criteria

Design 1

(conventional concrete)

Design 2

(internally cured concrete)

Alternative 1

($)

Alternative

1B ($)

Alternative 1

($)

Alternative

1B ($)

Initial material

price

213 213 223 223

Initial material

price adjusted

per total volume

458183.77 458183.77 436086.1385

436086.1385

Maintenance

over time

(MOT) at 5%

22909.188 22909.188 21804.30693 21804.30693

Design cost at

10%

45818.3776 45818.3776 43608.61385

43608.61385

Construction

inspection

services at 10%

45818.37769

45818.37769

43608.61385

43608.61385

Total at year

2017

572729.7212

572729.7212

545107.6732

545107.6732

Notably, the unit cost varies from one location to the other and from one project to the

other, based on total quantity. Therefore, the values used in this study are specific for this

project. The total maintenance and rehabilitation schedule for this project is illustrated in

Table 68. A total analysis period of 60 years is presented. The study used a discount rate of

3% (Rao & Darter, 2003). The project occurred at year 2013. Therefore, the values were

discounted one more time to the year 2017 to evaluate the net present value. As illustrated in

Table 68, the maintenance and rehabilitation items are different for both alternatives; since

the deterioration rate is different.

201

Table 68. Maintenance and rehabilitation activities schedule for both alternatives (Rao &

Darter, 2003)

Conventional concrete 11 inch Internally cured concrete 10 inch

Age Actual year # of punchout

repair

Age Actual year # of punchout

repair

15 2028 4 15 2028 4

25* 2038 5 25* 2038 5

42 2055 19 40 2053 6

50** 2063 50 60** 2073 17

*The maintenance activity includes diamond grinding

**The maintenance activity includes repair and structural rehabilitation with HMA

overlay

A detailed example for the maintenance and rehabilitation activities is illustrated in

Table 69 and will be examined step by step. The maintenance and rehabilitation cost items

are given along with the associated year. To get the total price for a certain activity for full

depth pavement design, the total quantity is multiplied by the unit price: 32 yd2 × 200 $/yd2 =

$6400. Moreover, an additional cost will be added, such as maintenance over time (MOT) at

5%, which is calculated as (5/100) × $6400 = $320; and design cost for 10%, which is

calculated as (10/100) ×$6400 = $640. Also, there are construction and inspection services,

which account for 10% and may be calculated as (10/100) × $6400 = $640. The total value is

$8000 at year 2028 (or at year 15). By discounting this value to the current year (2017), using

a discount rate of 3%, the resulting value is $8000/(1+0.03)11 = $5779.4. The final

maintenance and rehabilitation activity for Alternative 1 (conventional concrete) is illustrated

in Table 69. This accounts for $676,431 over a design life of 60 years at the year 2013 (Rao

& Darter, 2003).

202

Table 69. Detailed maintenance and rehabilitation activities for conventional concrete

Age from

project start

year

Activity Quantity Unit Unit price

($)

Total

($)

15 Diamond grinding existing

surface

0 yd2 5.60 0

15 Full depth pavement design 32 yd2 200 6400

15 MOT at 5% 320

15 Design cost at 10% 640

15 Construction inspection

services at 10%

640

Total 8000

25 Diamond grinding existing

surface

22293 yd2 5.60 124843

25 Full depth pavement repair 4 yd2 200 800

25 MOT at 5% 6282

25 Design cost at 10% 12564

25 Construction inspection

services at 10%

12564

25 Total 157053

42 Diamond grinding existing

surface

0 yd2 5.60 0

42 Full depth pavement repair 20 yd2 200 4000

42 MOT at 5% 200

42 Design cost at 10% 400

42 Construction inspection

services at 10%

400

Total 5000

50 Milling 0 yd2 3.50 0

50 Full depth pavement repairs 528 yd2 150 79200

50 Place asphalt tack coat (9

yd2/gal)

2477 gallon 1.70 4211

50 2 inch HMA binder 2475 tons 1.70 160846

50 2 inch HMA surface 2475 tons 65 160846

50 MOT at 5% 65 20255

50 Design cost at 10% 40510

Construction inspection

services at 10%

40510

Total 506378

Overall Total (all items) at

year 2013

676,431

Detailed analysis for the maintenance and rehabilitation activities for conventional

concrete are attached in Appendix F. The use of internally cured concrete resulted in a lower

lifecycle cost analysis and higher savings. This is due to the better qualities and higher

203

durability of internally cured concrete, resulting in lower maintenance and rehabilitation as

well as a higher salvage value, compared to conventional concrete. The total lifecycle cost

analysis for each alternative is illustrated in Table 70.

Table 70. Final lifecycle cost analysis for both alternatives

Cost item

Control section

11 inch CRCP

Internally cured concrete

10 inch CRCP

Total

cost at

2013

Net present

worth (2017)

Total

cost at

2013

Net present

worth (2017)

Total initial

cost 572729.7212 545107.6732

Total M&R

cost (1-60

years)

676433 761331.3009 608133 684459.0492

Salvage value

at year 60 -57754 -65002.63581 -75002 -84415.411

Net present

value (year

2017)

1269058.386 1145151.311

To get a final total score for each alternative, Equation 16 should be used.

Score for economic impact alternative i = NPVi/(∑NPVa)

The score is the net present value for the alternative, divided by all the net present value for

all alternatives. For example, for Design 1 and Alternative 1, the economic score =

1269058.386/ (1269058.386+1269058.386+1145151.311+1145151.311) = 0.2628. In this

case study, the user assigned a weight of 0.5 for the economic impact vs. the environmental

impact. Therefore, the values for the economic impact must be adjusted.

This can be performed using Equation 17.

EconW × Score for Economic impact alternative i

For example, for Design 1 and Alternative 1, the final economic score = 0.2628 × 0.5 =

0.134. The final economic values are illustrated in Table 71. From this analysis, Design 2 is

204

more economic than Design 1. This is because Design 2 has a lower thickness and higher

durability; these attributes were converted into a lower maintenance and rehabilitation cost in

the long term.

Table 71. Total lifecycle cost analysis per design and alternative

Design 1 conventional concrete Design 2 internally cured concrete

Alternative 1 Alternative 1B Alternative 2 Alternative 2B

1269058.38 1269058.38 1145151.31 1145151.31

Table 72. Final economic score per alternative

Design 1 Design 2

Alternative 1 Alternative 1B Alternative 2 Alternative 2B

Economic 0.2628 0.2628 0.2371 0.2371

Weighted

economic

score

0.1314

0.1314

0.1185

0.1185

5.2.9 TOTAL SUSTAINABILITY SCORE

The total score is illustrated in Table 73. As illustrated, Design 2 and Alternative 2B is the

best alternative, due to the lower total score (environmental and economic).

Table 73. Total sustainability score

Required score Design 1 Design 2

Alternative 1 Alternative 1B Alternative 2 Alternative 2B

Weighted

economic score

0.131

0.131

0.118

0.118

Weighted

environmental

score

0.138

0.136

0.114

0.112

Total score 0.269 0.267 0.233 0.231

5.2.10 STATISTICAL ANALYSIS

To be able to compare statistical significance of the results, another EPD will be used

to assess the environmental impact. Note that the economic impact cannot be compared

because cost data does not exist for states other than Louisiana. A compressive strength value

205

of 7000 psi will be used to evaluate the following environmental impact/inventory values:

GWP, ODP, AP, EP , POCP, RE and NRE.

The scope will include the following stages: raw material extraction, transportation

from raw material extraction to manufacturing, manufacturing, and transportation from

manufacturing to project location. The total environmental score will be compared, since the

breakdown for EPD is not available for states other than Louisiana. The same procedure will

be followed to evaluate the total environmental impact with the same assumptions, only raw

data from EPD will change. The raw data used, extracted from EPD, for compressive strength

value of 7000 psi are illustrated in Table 74 as a sample.

Table 74. Total environmental impact per alternative

Alternative GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

1 256.44 4.49E-06 5.67 0.55 82.61 2191.03 35.28

1B 230.47 4.43E-06 3.71 0.42 56.64 1813.35 32.28

2 346.35 4.29E-06 2.59 0.09 38.38 2190.03 34.26

2B 347.88 4.38E-06 2.59 0.09 38.61 1812.35 31.25

Average 295.28 4.3975E-06 3.64 0.28 54.06 2001.69 33.26

Final results for the environmental score are illustrated in Table 75. To better

understand the data used, descriptive statistics is illustrated in Table 76, including the mean,

the standard deviation, and confidence interval. To evaluate results significance, analysis of

variance (ANOVA) is performed with a confidence interval of 95%. Results are illustrated in

Table 77. The resulting P value =1 ( > 0.001 indicating insignificance of the results).

206

Table 75. Environmental impact comparison

Alternative Environmental

score (Texas)

Environmental

score

(7000 psi)

1 0.138 0.139

1B 0.136 0.134

2 0.114 0.115

2B 0.112 0.112

Mean 0.125 0.125

Standard

deviation 0.013491 0.013491

Table 76. Descriptive statistics for the environmental impact values

Criteria Texas data

7000

psi

Mean 0.125 0.125

Standard Error 0.006745 0.006745

Median 0.1245 0.1245

Standard Deviation 0.013491 0.013491

Sample Variance 0.000182 0.000182

Kurtosis -5.09341 -5.09341

Skewness 0.074939 0.074939

Range 0.027 0.027

Minimum 0.112 0.112

Maximum 0.139 0.139

Sum 0.5 0.5

Count 4 4

Confidence

Level(95.0%) 0.021467 0.021467

Table 77. Analysis of variance results

Source

of

Variation SS

Degrees

of

freedom

(df) MS F P-value F critical

Between

Groups 0 1 0 0 1 5.987378

Within

Groups 0.001126 6 0.000188

Total 0.001126 7

207

5.3 CASE STUDIES IN LOUISIANA

The Louisiana Department of Transportation and Development (LaDOTD) is

responsible for maintaining more than 17,000 miles of state U.S. and interstate highway

pavement structure (Wu & Xiao, 2016). This study was supported by the Louisiana

Transportation and Research Center (LTRC) and the Louisiana Department of Transportation

and Development (LaDOTD). The study will analyze various projects previously performed

by LaDOTD. Case studies were extracted from LaDOTD past and current projects. This

section will provide a step by step demonstration of the case studies performed from the

moment the case study was extracted for analysis, until the final decision making criteria.

5.3.1 CASE STUDY 1 : ALTERNATIVE DESIGN COMPARAISION

5.3.1.1 Project description

This project falls under a proposal number of H.003432. The project is titled Interchange

Improvements @ I-12 & U.S 51 Bus. The project is in Tangipahoa Parish, Hammond district,

with a zip code of 70454.

5.3.1.2 Project properties

Project properties such as a) traffic data, b) directional distribution, c) truck distribution,

d) design speed, e) average daily traffic, and f) K factor are illustrated in Table 78. The

project is divided into two roads: The U.S 51 bus and the I-12 Westbound exit ramp. The

directional distribution, the K factor, and the design speeds are the same in both roads.

However, other factors, such as the 2012 average daily traffic and the 2032 average daily

traffic, are different.

208

Table 78. Traffic data criteria (LaDOTD)

Criteria U.S 51 bus I-12 Westbound

exit ramp

D (Directional distribution) 55% 55%

K 10% 10%

T (truck distribution) 8% 18%

Design speed (MPH) 40 40

2012 Average Daily Traffic

(A.D.T.)

22300 7000

2032 A.D.T 29900 11300

5.3.1.3 Design properties

The design and thicknesses are illustrated in Figure 48. The layers input are as follows:

Portland cement concrete layer, a class 2 Base course (crushed stone, recycled PCC, or

blended calcium sulfate, and a Subbase layer of lime treatment type E. The PCC modulus of

rupture is 600 psi.

Figure 47. Design layers

5.3.1.4 Environmental impact

To evaluate the environmental impact of this project, a developed framework will be

used. The solution will be provided in detail, step by step.

1. Select the state you want to search for the mix design: The state is Louisiana.

Portland

cement

concrete

11 inch

Class 2 Base

Course

8 inch

Lime

Treatment

12 inch

209

2. The purpose of the design is to present an alternative design comparison. The stakeholder

is interested in evaluating the environmental impact of various alternatives. These

different alternatives consist of various mix designs.

3. Select the number of designs to evaluate: only one design.

4. Select the number of mixes to evaluate: 3 PCC mix designs.

5. Assign weights for the environmental and economic impacts. Both impacts will be

assigned a weight of 0.5.

6. Convert the modulus of rupture to compressive strength value, using Equation 8, where:

MOR (psi) = 2.3 (fc)2/3 or fc= (MOR/2.3)3/2. This results in a compressive strength value

of (600/2.3)3/2 = 4213 psi

7. Select alternative mixes from the EPD data to evaluate the environmental impact. The

user enters a specific mix design (required by the design) to look for the environmental

impact in the database. This mix design is illustrated in Table 79. Normally, the paving

mix designs have a cement content ranging from 400 to 550 lbs. The input value for the

cement content should be in this range.

Table 79. Required mix design

Compressive

strength

value (psi)

Cement

(lb)

Fly

ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate

1 (lb)

Coarse

aggregate

2 (lb)

Mixing

water

(gallons)

Air

entertainer

(%)

4213 412 102 1400 1600 1420 32 1

This exact mix design is not in the database; therefore, the stakeholder may select

from among the existing mixes. The nearest mixes, based on the cement and fly ash contents,

are illustrated in Table 80. All these mixes have a compressive strength value above 4213 psi.

As illustrated in Table 80, there are various mix designs, but there should be some filtering

criteria

For example, the stakeholder can select one of the filtering criteria to be the proximity

to the project location (providing less environmental impact and less time for transportation).

210

The manufacturers in Hammond can provide a good selection criteria, since the project is in

Hammond. The selection of the Hammond district would narrow the mixes to options 6, 7, 8,

9, and 10. The new selections are illustrated in Table 80.

Another filtering criteria can be the initial cost. For example, the user can select the

top three mixes with the least cost. This will narrow down the search criteria to mixes 6, 7,

and 9, as illustrated in Table 81. These are the mixes which will proceed to the environmental

impact evaluation.

The environmental impact of the mixes 6, 7, and 9 are illustrated in Table 83. These

are the values extracted from EPD with no modifications. As illustrated, the values are given

per 1 yd3. These are the impacts for A1: raw material extraction and A3: manufacturing.

These values are given per 1 yd3; some adjustments must be performed to adjust the

environmental impacts per the total design volume. The total design volume calculation is

illustrated in Table 84, for the 11 inch thickness.

The calculation was performed using Equation 6: Lv = LT×LW× LL. The total environmental

impact for the design then should be adjusted according to the overall design volume, using

Equation 7:

For example, the total adjusted GWP, for alternative 6 = the volume 2151.09 yd3 × 194.079

kg CO2 eq/yd3= 417482.804 kg CO2 eq

The environmental impact will be adjusted accordingly for each alternative. Final

results are indicated in Table 85. As illustrated, the values have different units. Therefore,

these should be normalized to present consistent, unitless units, that can be summed up

altogether in the end. The normalization values used are illustrated in Table 86.

211

Table 80. Corresponding mix design

Alternative

Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

Water

reducer

(oz)

District

Initial

cost

($/yd3)

1 414 103 1,180.00 1,481.00 413 29.6 20.7 Baton Rouge 123

2 414 103 1,291.00 1,559.00 413 31 20.7 Baton Rouge 123

3 414 103 1,092.00 1,353.00 846 30.3 15.51 Baton Rouge 123

4 414 103 1,285.00 1,379.00 607 31 20.7 Baton Rouge 117

5 414 103 1,281.00 1,376.00 604 31 20.7 Baton Rouge 117

6 413 104 1,483.00 1,421.00 320 31 15.51 Hammond 106

7 414 103 1,399.00 1,652.00 0 30 20.68 Hammond 120

8 414 103 1,092.00 1,475.00 715 30.3 15.51 Hammond 123

9 414 103 1,362.00 1,682.00 0 30 20.68 Hammond 106

10 413 104 1,483.00 1,438.00 320 31 20.68 Hammond 220

11 414 103 1,000.00 1,483.00 550 29.7 30.2 Lafayette 116

12 414 103 1,521.00 1,521.00 0 29.5 31.2 New Orleans 106

Table 81. Filtering criteria based on manufacturer location

Alternative

Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Water

reducer

(oz)

Initial

cost

($/yd3)

6 413 104 1,483.00 1,421.00 320 31 15.51 106

7 414 103 1,399.00 1,652.00 0 30 20.68 120

8 414 103 1,092.00 1,475.00 715 30.3 15.51 123

9 414 103 1,362.00 1,682.00 0 30 20.68 106

10 413 104 1,483.00 1,438.00 320 31 20.68 220

212

Table 82. Filtering criteria based on cost

Alternative

Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Water

reducer

(oz)

Initial

cost

($/yd3)

6 413 104 1,483.00 1,421.00 320 31 15.51 106

7 414 103 1,399.00 1,652.00 0 30 20.68 120

9 414 103 1,362.00 1,682.00 0 30 20.68 106

Table 83. Environmental impact extracted from EPD (Al and A3)

Alternative GWP

kg CO2eq/yd3

ODP

kg CFC-11 eq/yd3

AP

kg SO2 eq/yd3

EP

kg N eq/yd3

POCP

kg O3 eq/yd3

NRE

MJ/yd3

RE

MJ/yd3

6 194.079 3.23E-06 0.801 0.088 13.133 1399.590 157.365

7 194.076 3.34E-06 0.801 0.088 13.133 1399.522 157.344

9 193.893 3.23E-06 0.802 0.088 13.145 1400.768 157.492

Table 84. Final layer volume

Dimension Value Unit Unit conversion Final unit

Layer Thickness 11 Inch 1/36 Yd

Length 1 Mile 1760 Yd

Width 12 Feet 0.33 Yd

Total volume 2151.09 Yd3

213

The normalization can be performed by dividing the environmental impact per the

normalization value. This can be accomplished by following Equation 2

Normalized value = environmental impact/normalization value

For example, the normalization value for the GWP for alternative 6 =

417482.804 kg CO2 eq/24000 kg CO2eq = 17.39. Final values are illustrated in Table 87.

Table 85. Adjusted environmental impact per volume

Alternative GWP

kg CO2 eq

ODP

kg

CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3 eq

NRE

MJ

RE

MJ

6 417482.80 0.006 1723.97 189.39 28249.55 3010654.00 338507.89

7 417476.45 0.006 1723.95 189.39 28251.41 3010508.34 338463.66

9 417082.24 0.006 1724.60 189.51 28276.42 3013189.54 338780.86

Table 86. Normalization values used

GWP(kg CO2eq/ yd3) 24000

ODP(kg CFC-11 eq/yd3) 0.160

AP(kg SO2 eq/yd3) 91

EP(kg N eq/yd3) 22

POCP(kg O3 eq/yd3) 1400

NRE(MJ/yd3) 288572.509

RE(MJ/yd3) 24874.54785

Table 87. Normalized value for adjusted environmental impact per total volume

Alternative GWP ODP AP EP POCP NRE RE

6 17.39 0.037 18.94 8.60 20.17 10.43 13.60

7 17.39 0.037 18.94 8.60 20.18 10.43 13.60

9 17.37 0.037 18.95 8.61 20.19 10.44 13.62

5.3.1.5 Transportation impact

Transportation from the raw material extraction to the manufacturing phase. These are given

per Athena Institute for each mix design. The values are given per 1 yd3. The values are

illustrated in Table 88. These values should be adjusted to total design volume.

214

Table 88. Transportation from raw material extraction to manufacturing phase (A2)

Alternative GWP

kg CO2

eq/ yd3

ODP

kg CFC-11 eq/

yd3

AP

kg SO2 eq/

yd3

EP

kg N eq/

yd3

POCP

kg O3 eq/

yd3

NRE

MJ/

yd3

RE

MJ/

yd3

6 23.53 0.00 0.164 0.009 4.66 322.70 0.00

7 23.62 0.00 0.165 0.009 4.68 323.99 0.00

9 24.48 0.00 0.170 0.010 4.83 335.73 0.00

The adjustment process is illustrated in Table 89, which is performed by multiplying

the values in Table 84 by the total design volume. For example, the adjusted GWP for

alternative 6 = 23.535 kg CO2 eq/ yd3×2151.09 yd3 = 50625.655 CO2 eq

Table 89. Adjusted transportation impact per design volume

Alternative GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

6 50625.65 0.00 352.75 19.73 10035.23 694178.65 0.00

7 50827.32 0.00 354.01 19.80 10070.86 696944.58 0.00

9 52669.24 0.00 365.63 20.45 10396.84 722204.51 0.00

Part 2: Transportation impact from the raw material extraction to project location

To calculate the transportation impact from the raw material extraction to project location, the

distance between the manufacturers to project location should first be determined. This can

be accomplished by calculating the distance between the two zip codes of the project

location, as well as the manufacturer location. The zip code of the project location is 70454

and the manufacturer zip codes are presented in the EPD for each mix design. Table 90

illustrates the project zip code, the manufacturer zip code, and the distance between the

project and the manufacturer location (calculated through Google maps). Results in Table 90

indicate that the transportation values are almost identical, since the manufacturer is in the

Hammond area for all alternatives.

215

Table 90. Total transportation distance (manufacturer to project location)

Alternative

number

Project

location

Manufacturer

location

Total distance

(miles)

Total distance

(km)

6 70454 70471 37 60

7 70454 70726 36 58

9 70454 70471 37 60

The transportation will be performed using a heavy duty truck with a weight of

80,000 lb and diesel fuel. The total weight of concrete to be transported is illustrated in Table

81. These values exist in the database and were gathered from the manufacturer. To obtain

the total weight of the concrete transported, Equation 9 should be used: M = D ×Lv

For example, the density for alternative 6 = 4000.81lb/yd3 and the total design volume

= 2151.09 yd3; therefore, the total design weight = 4000.81lb/yd3×2151.09 yd3 =8606152.733

lb; then this weight value should be converted to metric ton, which will be accomplished

through multiplying the value by 0.00045359. Total design weight = 8606152.733 lb ×

0.00045359 = 3903.664818 ton. The total weight to be transported for each alternative is

therefore the sum of truck weight as well as the transported concrete. Final values are

illustrated in Table 91.

To obtain the total number of loads required, Equation 10 should be used.

For example, for alternative 6, the total number of loads = 8606152.73 lb/54000 lb = 159.37

loads

Table 91. Weight of concrete to transport

Alternative

number

Density

(lb/yd3)

Total weight per

design volume of

concrete

(lb)

Weight

of

concrete

(ton)

Total

number

of loads

Total

weight

(truck+

concrete)

(ton)

6 4000.81 8606152.73 3903.66 159.37 3939.95

7 3819.91 8217016.49 3727.15 152.16 3763.44

9 3812.92 8201966.88 3720.33 151.88 3756.61

216

To adjust the inventory values coming from the transportation module, Equation 11 should be

used:

× total number of loads

The emissions/inventory for the heavy duty truck is illustrated in Table 92.

Table 92. Heavy duty truck emissions

GWP

kg CO2 eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

3.24E-01 0.00E+00 1.34E-03 5.55E-04 4.62E-02 8.09E-02 0.00

For example, to calculate the transportation impact from the manufacturing to the

project location for GWP for alternative 6:

Adjusted inventory values = 2 × 0.324 kg CO2/ton.km (3939.952ton) × 60 km × 159.37

loads= 24088122.57kg CO2 eq. The adjusted inventory per design alternative is indicated in

Table 93.

Table 93. Transportation impact from the manufacturer to project location

Alternative GWP

kg CO2 eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

6 24088122.57 0.00 99623.71 41262.06 3434787.84 6014596.03 0.00

7 21374862.61 0.00 88402.21 36614.34 3047897.07 5337118.47 0.00

9 21888597.91 0.00 90526.91 37494.35 3121151.92 5465393.73 0.00

Total transportation impact. The total transportation impact is the sum of Part 1

(transportation from raw material extraction to manufacturing), and Part 2 (transportation

from the manufacturer to project location). Values are illustrated in Table 94. These values

should be normalized.

To normalize the total transportation impact values, each value should be divided by

the corresponding normalization value.

217

For example, alternative 6 will have the following value after normalization (for GWP) =

24138748.233kg CO2 eq/ 24000 kg CO2 eq = 1005.781

The total transportation values are illustrated in Table 95 for the three alternatives.

5.3.1.6 Total environmental impact

The total environmental impact is the total of the environmental impact from concrete design

(EPD), as well as the total transportation impact (from raw material extraction to

manufacturing and from manufacturing to project location). This will result from the values

given in Table 96.

For example, the environmental impact extracted from EPD and adjusted, based on

design volume, was previously described:

Environmental impact from EPD (adjusted per volume) + total transportation impact. =

417482.80 kg CO2 eq + 24138748.233kg CO2 eq = 24556231.037 kg CO2 eq. These total

environmental impacts must be normalized. Values after normalization are illustrated in

Table 97.

5.3.1.7 Weighing the environmental impact

Based on stakeholder preference, weighting can be assigned to the impacts. The weighting

procedure will be used here for demonstration. Default weights were used for this case. The

weights are illustrated in Table 98.

Equation 3 can be used to convert the environmental impacts into weighted

environmental impacts: weighted impact = assigned weight × normalized value

For example, for alternative 6 = 1023.176× 0.200 = 204.635

218

Table 94. Total transportation impact per alternative

Alternative GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

6 24138748.23 0.00 99976.46 41281.79 3444823.08 6708774.69 0.00

7 21425689.94 0.00 88756.22 36634.15 3057967.93 6034063.05 0.00

9 21941267.15 0.00 90892.55 37514.80 3131548.76 6187598.25 0.00

Table 95. Total transportation impact per alternative normalized

Alternative GWP ODP AP EP POCP NRE RE

6 1005.781 0.000 1098.642 1876.445 2460.588 23.24 0.00

7 892.737 0.000 975.343 1665.189 2184.263 20.91 0.00

9 914.219 0.000 998.819 1705.219 2236.821 21.44 0.00

Table 96. Total environmental impact per alternative

Alternative

GWP

kg CO2 eq

ODP

kg CFC-11 eq

AP

kg SO2 eq

EP

kg N eq

POCP

kg O3 eq

NRE

MJ

RE

MJ

6 24556231.03 0.006 101700.44 41471.19 3473072.63 9719428.69 338507.89

7 21843166.39 0.006 90480.17 36823.54 3086219.34 9044571.40 338463.66

9 22358349.40 0.006 92617.15 37704.32 3159825.18 9200787.80 338780.86

Table 97. Normalization values for the total environmental impacts

Alternative GWP ODP AP EP POCP NRE RE

6 1023.17 0.037 1117.58 1885.05 2480.76 33.68 13.60

7 910.13 0.037 994.28 1673.79 2204.44 31.34 13.60

9 931.59 0.037 1017.77 1713.83 2257.01 31.88 13.62

219

Table 98. Weights used in the study

GWP ODP AP EP POCP NRE RE Total

0.200 0.150 0.150 0.150 0.150 0.100 0.100 1

At this point in time, the values are on the same scale (because of normalization,

which put all the values on the same scale as well as unitless). The total environmental score

is the sum of all the environmental values together, then the RE value is deducted: Total

environmental score = GWP+ODP+AP+POCP+NRE-RE = 1029.159

The relative score is the environmental impact score compared for each alternative

with respect to other alternatives. This can be accomplished through Equation 14

Score for environmental impact for each alternative =

Total environmental score for alternative i/ ∑Environmental impact for all alternatives

For example, the score for alternative 6 = score for environmental 6 / sum of all scores

= 1029.159/ (1029.159+914.685+936.445) = 0.357

This equation was repeated for all other alternatives. Values are illustrated in Tables

99 and 100. In this case, the alternative having the lowest score is the one that has the lowest

environmental impact. Alternative 7 is the alternative with the lowest environmental impact.

Should the stakeholder be assigned a weight for the environmental score (the case in this

study, since the assigned weight is 0.5), then the final environmental score after adjusting per

the weight can be calculated, using Equation 15.

Weighted environmental score per alternative = EnvW × score for environmental

impact for alternative. For example, for alternative 7, the weighted score = 0.5 × 0.357=

0.179. In this instance, alternative 7 has the lowest environmental impact

220

Table 99. Total environmental impact after normalizing and weighting

Alternative GWP ODP AP EP POCP NRE RE Total

6 204.635 0.006 167.638 282.758 372.115 3.368 1.361 1029.159

7 182.026 0.006 149.143 251.070 330.666 3.134 1.361 914.685

9 186.320 0.006 152.666 257.075 338.553 3.188 1.362 936.445

Table 100. Relative score and environmental score

Alternative Relative

score

Assigning

environmental

score

6 0.357 0.179

7 0.317 0.159

9 0.325 0.163

5.3.1.8 Economic impact

As previously described, the economic analysis will be performed by completing a full

lifecycle cost analysis for each alternative. This lifecycle cost analysis consists of an initial

cost (occurring at the present) and a maintenance and rehabilitation cost occurring in the

future. The economic analysis will follow the maintenance and rehabilitation schedule for the

State of Louisiana, previously illustrated in the literature review. This schedule is illustrated

in Table 101.

The total analysis period to study the project is 50 years; the project start year is 2017,

for the maintenance and rehabilitation items. Based on this schedule at year 20, there are

items such as cleaning and sealing joints and patching. In year 30; there is patching as well.

This addresses the schedule and items that will be selected. At year 50, this is the end of life,

and there is no salvage value. Also, in addition to this schedule, saw cutting will be added in

years 20 and 30 of the project start year. This is to demonstrate the available items in the

database.

221

Table 101. Maintenance and rehabilitation schedule for the State of Louisiana

The initial material price (collected from the manufacturer) is illustrated in Table 102.

Values are given per 1 yd3. To adjust the material price per total design volume, the price per

1yd3 is multiplied by the total volume. For example, for alternative 6, this will equal

106$/yd3×2151.09 yd3 = $228016.33

Table 102. Material price adjusted per volume

Alternative

number

Material

price

$/yd3

Adjusted material

price per total

design volume

6 106 228016.33

7 120 258131.70

9 106 228016.33

The initial cost (from the bidding) exists for all the mix designs. The values are

illustrated in Table 103. As may be seen, these mix designs were originally used in projects

with various thicknesses. For example, alternative 6 was previously used in a project with a

paving thickness of 9 inch. However, the unit price is given in terms of volume in order to fit

various thicknesses. In the unit conversion for example, if the item is given in terms of area

and the thickness is provided, the item is then converted to units of volume by multiplying

the area × thickness. The total bid cost for this item is divided by the total volume, to get the

price per unit volume.

The letting date is provided, which may be used to calculate the time value of money

for this mix design, as well as to compare them at the same point in time for example, at year

2017. This can be accomplished by using the net present value equation (Equation 4).

Project Type Alternate Year 0 Year 15 Year 20 Year 30 Year 50

Interstate

New

Construction

Rigid New JPC

Pavement

No

Action

Clean/Seal

Joints

Patch 1%

of Joints

Retexture

Patch 3%

of Joints

End of

life.

No

salvage

value.

222

For example, for alternative 6: The total price = $328× (1+0.04)4 = $383.713; to

account for the total design volume, this cost should be multiplied by the total design volume.

This will result in the following value: 383.713 $/yd3 ×2151.09 yd3 = $825401.2 All adjusted

values are illustrated in Table 104.

As for the maintenance and rehabilitation items, the compressive strength value of the

selected mixes will be matched to the compressive strength value for past projects (applying a

tolerance of 10%), and the maintenance and rehabilitation items will be matched accordingly.

Depending on data availability, the perfect case would be to match the compressive strength

value for recent projects, with the compressive strength value of older projects. Should the

mix design of the past project be available, it would be advantageous to match both mix

design breakdowns and select maintenance and rehabilitation activities based on both the

compressive strength and mix design breakdowns.

The selected mixes have a compressive strength value of 5540, 4800, and 5530.

Matched past projects with these compressive strength values are indicated in Table 105 for

each alternative, and a detailed example is provided for alternative 6. As illustrated in Table

105, based on the selected tolerance, there are various compressive strengths as well as a mix

design breakdown. All these compressive strengths are above the required compressive

strength value, and therefore, any compressive strength value can be safe to use.

The next step is to match the mix design breakdown for available mixes. Table 106

illustrates the matching projects based on the compressive strength values and whether they

have a mix design breakdown. For the projects that have a mix design breakdown and to

match both mix designs (with a tolerance up to 10% for the cement value, the closer the

match to the original mix, the better), the first step is to look at the cement content. As can be

seen, project H.007116.6 has the closer cement content. In this case, project H.007116.6 will

be selected based on a matched mix design breakdown.

223

Table 103. Initial cost items

Alternative

number Letting date Parish

name Item Description

Bid unit price

at letting date

per yd3

Compressive

strength value

(psi)

6 10/9/2013 Tangipahoa Portland Cement Concrete

Pavement (9" Thick)

$328.00 5540

7 11/14/2012 Tangipahoa Portland Cement Concrete

Pavement (9" Thick)

$460.00 4800

9 2/29/2012 St. Tammany Portland Cement Concrete

Pavement (12" Thick)

$210.00 5530

Table 104. Initial cost items per alternative

Alternative

number Letting date

Parish

name Item Description

Bid unit price

at letting date

per yd3

Net present value at

year 2017 for the

bid unit price

($)

Bid unit price discounted to

current year (2017) and

adjusted per total design

volume ($/design)

6 10/9/2013 Tangipahoa

Portland Cement

Concrete Pavement

(9" Thick)

$328.00 383.71

825405.399

7 11/14/2012 Tangipahoa

Portland Cement

Concrete Pavement

(9" Thick)

$460.00 559.66 1203883.97

9 2/29/2012 St.

Tammany

Portland Cement

Concrete Pavement

(12" Thick)

$210.00 255.49 549599.20

224

Table 105. Projects associated with the selected compressive strength value alternative 6

Compressive

strength value

(psi)

Project ID Mix design

available?

5540 H.009572.6 No

5540 H.009342.6 No

5540 H.007265.6 No

5560 H.006622.6 No

5560 H.010486.6 No

5560 H.000466.6 No

5560 H.010396.6 No

5638 H.007116.6 Yes

5893.8 013-06-0034 Yes

5947.10 025-06-0027 Yes

5707.93 742-06-0016 Yes

5821.24 808-07-0035 Yes

Table 106. Matching mix design alternative 6

Proposal ID

Compressive

strength value

(psi)

Cement

(lb)

Fly

ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Air

entertainer

(%)

H.007116.6 5638 424 106 1018 1242 600 31.6 3.5

013-06-0034 5893.8 429 107 1275 1599 0 32 4

025-06-0027 5947.1 445 110 1589 1400 0 31.9 3.5

742-06-0016 5707.9 437 109 1158 1850 0 30 5

808-07-0035 5821.2 437 109 1119 1875 0 31.3 4.91

225

A detailed example is provided in Table 107 for the maintenance and rehabilitation

activities. All the maintenance and rehabilitation activities for all matching projects are

provided. As can be seen, the maintenance and rehabilitation projects occurred in various

districts. Having compared all the items at the same point in time, the bid unit price will vary

by location as well as by total quantity for the same activity. For example, the higher the total

quantity, the lower the unit price. Since the cost varies by location, it is recommended to

choose maintenance and rehabilitation activities occurring in the same district and parish.

Also, it is recommended to select similar quantities. For example, if a project has an area of

16.1 yd2 and a thickness of 11 inch, it is recommended to select matching projects with a

similar area (16.1 yd2) and thicknesses (11 inch).

The selection depends on the user; for example, one scenario is to select maintenance

and rehabilitation items that occurred in the same district or parish to guarantee similar price.

Another scenario is to select the project with a matching mix design breakdown and assume

that both mixes will behave similarly on the long term (in this case, project H.007116.6). In

the event there are not many items for the selected mix design, the user might go further and

select other projects with an available mix design breakdown. In this case, the cement content

might rise Another scenario would be to select the lowest maintenance and rehabilitation

option, after discounting all alternatives at the same point in time.

All the maintenance and rehabilitation activities are converted to the year 2017, so

that the user can compare. As can be seen, the data availability itself is of paramount

importance and this is the main criteria to affect the user selection. Values discounted are

presented in Table 107. The final user selection criteria are also illustrated. However, this

cost only performs as a guide, so the final actual prices might vary by district and parish and

layer thickness. As discussed, the selection criteria is also subject to data availability and will

be discussed later in limitations and future work.

226

As for detailed calculations: The project starts at year 2017; the design life is 50

years; and the discount rate used is 4%. For example, for alternative 6 and project

H.010486.6, the full depth patching JPCP (16.1 square yards to 48.0 square yards) (10" thick)

has a value of $377.96, which occurred at the year of 2014. To get the present value of this

amount at current year 2017, this value is converted by 377.96×(1+0.04) (2017-2014) = $425.164,

which is illustrated in Table 107. The same methodology was used for all the other activities

and alternatives. All the values were converted from the letting date to the year 2017, for a

strong comparison at the same point in time. The same discount rate was used in all cases.

The selection criteria here will be as follows: first, the items are going to be selected

from Hammond district (since the project is already in Hammond). In case the Hammond

district does not have all the maintenance and rehabilitation items required, the user might

refer to other districts for guidance. Selected items have a year of occurrence in the table as a

user input. In this case study, the user is interested in getting three maintenance and

rehabilitation activities for all the three alternatives: full depth patching of jointed concrete

pavement (16.1 square yards and over) occurring at years 20 and 30, cleaning and sealing

random cracks occurring at year 20, and saw cutting Portland cement concrete pavement at

years 20 and 30. Based on this assumption, the saw cutting was selected from Hammond

district. However, since the other items do not exist in Hammond district, they will be

selected from other districts based on the lowest cost. Final values are illustrated in Table 107

with the corresponding year of occurrence.

227

Table 107. Maintenance and rehabilitation item for alternative 6

Proposal

number and

district

Letting date

Item description

Price

at letting

date

($)

Unit

Net

present

value, year

2017

($)

Year of

occurrence

Cost at year

of

occurrence

($)

H.010486.6

(Alexandria)

9/10/2014

Full Depth Patching of Jointed

Concrete Pavement (16.0

square yards and under) (10"

Thick)

485.9611 Yd3 546.640

9/10/2014

Full Depth Patching of Jointed

Concrete Pavement (16.1

square yards to 48.0 square

yards) (10" Thick)

377.9697

Yd3 425.164 2047

1378.977

9/10/2014

Full Depth Patching of Jointed

Concrete Pavement (16.1

square yards to 48.0 square

yards) (10" Thick)

377.9697 Yd3 425.164 2037 931.58

9/10/2014

Full Depth Patching of Jointed

Concrete Pavement (48.1

square yards and over) (10"

Thick)

359.9712

Yd3 404.918

H.010396.6

(Monroe)

10/8/2014 Cleaning and Sealing Random

Cracks 11879.619 Mile 13362.95 2037 29279.88

10/8/2014

Full Depth Patching of Jointed

Concrete Pavement (16.0

square yards and under) (9"

Thick)

1199.9040

Yd3 1349.72

10/8/2014 Full Depth Patching of Jointed

Concrete Pavement (16.1 1139.9088

Yd3 1282.24

Table 107 (cont.)

228

Proposal

number and

district

Letting date

Item description

Price

at letting

date

($)

Unit

Net

present

value, year

2017

($)

Year of

occurrence

Cost at year

of

occurrence

($)

square yards to 48.0 square

yards) (9" Thick)

10/8/2014

Full Depth Patching of Jointed

Concrete Pavement (48.1

square yards and over) (9"

Thick)

959.92

Yd3 1079.78

H.000466.6

(Hammond)

5/13/2015

Saw Cutting Portland Cement

Concrete Pavement

1

INLF

1.08

2037 2.36

H.000466.6

(Hammond)

5/13/2015

Saw Cutting Portland Cement

Concrete Pavement

1

INLF

1.08

2047 3.50

H.006622.6

(Hammond)

8/21/2014

Cleaning and Resealing

Existing Longitudinal and

Transverse Pavement Joints

17423.44

Mile

19599.00

H.006622.6

(Hammond)

8/21/2014

Saw Cutting Portland Cement

Concrete Pavement

1.5

INLF

1.68

H.007265.6

(New Orleans)

10/12/2016

Cleaning and Resealing

Existing Longitudinal

Pavement Joints

5279.83 Mile 5491.02

H.007265.6

(New Orleans)

10/12/2016

Cleaning and Resealing

Existing Transverse Pavements

Joints

5279.83 Mile 5491.02

Table 107 (cont.)

229

Proposal

number and

district

Letting date

Item description

Price

at letting

date

($)

Unit

Net

present

value, year

2017

($)

Year of

occurrence

Cost at year

of

occurrence

($)

H.007265.6

(New Orleans)

10/12/2016

Cleaning and Sealing Random

Cracks 7919.74 Mile 8236.53

H.007265.6

(New Orleans)

10/12/2016

Saw Cutting Portland Cement

Concrete Pavement 1.5 INLF 1.56

H.007116.6

(Alexandria)

Saw Cutting Portland Cement

Concrete Pavement

1.5

INLF

1.75

H.009572.6

(New Orleans)

11/18/2015

Saw Cutting Portland Cement

Concrete Pavement

0.75

INLF

0.8112

H.009342.6

(Hammond)

7/8/2015

Saw Cutting Portland Cement

Concrete Pavement

1

INLF

1.0816

Net present value 14215.4

230

Following the same logic, all the matching projects based on compressive strength

values and or mix design breakdown were collected for alternative 7. Table 108 illustrates the

matching projects associated with the compressive strength value and whether these projects

have associated mix design breakdown. Table 109 illustrates the mix design breakdown for

the matched projects with mix design breakdown.

There are two projects with associated mix design breakdown (based on a tolerance

level of 10% for the cement value). Depending on preference, the user might proceed with

these alternatives. All the maintenance and rehabilitation activities for the projects in Table

110 are displayed. It should be noted that not all projects have maintenance and rehabilitation

activities. For example, projects 077-04-0015 and 451-01-0108 have no maintenance and

rehabilitation activities, only those costs associated with initial cost activities.

Maintenance and rehabilitation items from Hammond district will be selected first,

since the project is in Hammond, and then the rest of maintenance and rehabilitation activities

will be selected from other districts. Should two similar activities occur at the same parish,

the lowest cost item would be selected. Selected values have the year of occurrence

displayed. Values are illustrated in Table 110.

Table 108. Projects associated with the selected compressive strength value alternative 7

Compressive strength

value (psi) Project ID

Mix design

available?

4800 H.003298.6 No

4800 H.009546.6-R1 No

4800 H.009539.6 No

4900 077-04-0015 Yes

4890.4 102-01-0034 No

5100 451-01-0108 Yes

231

Table 109. Matching compressive strength value alternative 7

Proposal ID

Compressive

strength

value (psi)

Cement

(lb)

Fly

ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate

1 (lb)

Coarse

aggregate

2 (lb)

Mixing

water

(gallons)

Air

entertainer

(%)

077-04-0015 4900 436 109 1216 1769 0 31.3 4.09

451-01-0108 5100 482 120 1078 1426 357 35 5

Table 110. Maintenance and rehabilitation activities for alternative 7

Proposal

number and

district

Letting date

Item description

Price

at letting

date

($)

Unit

Net present

value, year

2017

($)

Year of

occurrence

Cost at year

of occurrence

($)

H.003298.6

(Monroe)

2/8/2017

Saw Cutting Portland

Cement Concrete

Pavement

1.19

INLF

1.19

2037

2.60

H.003298.6

(Monroe)

2/8/2017

Saw Cutting Portland

Cement Concrete

Pavement

1.19

INLF

1.19

2047

3.85

H.009546.6-R1

(Monroe)

12/16/2015

Cleaning and Sealing

Random Cracks

7655.75

Mile

8280.46

2037

18143.517

H.009539.6

(Alexandria)

3/12/2014

Full Depth Patching of

Jointed Concrete

Pavement (16.1 square

yards to 48.0 square

yards) (10" Thick)

395.968

Yd3

445.41

2047

1444.64

Table 110 (cont.)

232

Proposal

number and

district

Letting date

Item description

Price

at letting

date

($)

Unit

Net present

value, year

2017

($)

Year of

occurrence

Cost at year

of occurrence

($)

H.009539.6

(Alexandria)

3/12/2014

Full Depth Patching of

Jointed Concrete

Pavement (16.1 square

yards to 48.0 square

yards) (10" Thick)

395.968

Yd3

445.41

2037

975.94

102-01-0034

(Shreveport)

7/22/2009

Saw Cutting Portland

Cement Concrete

Pavement

5

INLF

5.62

Net Present Value

9173.66

233

As illustrated, Table 111 illustrates the projects with matching compressive strength

value and/or a mix design breakdown for alternative 9. After that, Table 112 displays the mix

design breakdown for the projects having a matched mix design breakdown. Depending on

data availability, maintenance and rehabilitation items are illustrated in Table 113. There are

two projects matching the compressive strength value and with associated mix designs.

However, the projects with associated mix design breakdown have no maintenance and

rehabilitation activities. Therefore, the user must select the maintenance and rehabilitation

items from the remaining projects.

Table 111. Projects associated with the selected compressive strength value alternative 9

Compressive

strength value

(psi)

Project ID Mix design

available?

5530 H.011678.6 No

5540 H.009341.6 No

5530 H.009598.6 No

5560 H.010486.6 No

5534 024-04-0013 Yes

5532 019-04-0036 Yes

The maintenance and rehabilitation items are illustrated in Table 113, for projects

having maintenance and rehabilitation activities. For example, Project 024-04-0013, 019-04-

0036 have no maintenance and rehabilitation activities. The selected items have the year of

occurrence as a user input.

5.3.1.9 Final weight for the economic impact

The final weight for the economic impact will be performed using the sum of initial

cost and maintenance and rehabilitation cost. Values for each alternative are illustrated in

Tables 114 and 115. There are two scenarios here. The first scenario is to calculate the total

cost with respect to the initial cost and pertaining to the material only.

234

Table 112. Matching compressive strength value alternative 9

Proposal ID

Compressive

strength value

(psi)

Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Air

entertainer

(%)

024-04-0013 5534 436 109 1290 1887 0 32.9 0

019-04-0036 5532 476 0 1280 1052 359 27.2 2.5

Table 113. Maintenance and rehabilitation activities for alternative 9

Proposal

number and

district

Letting date

Item description

Price

at letting

date

($)

Unit

Net present

value, year

2017

($)

Year of

occurrence

Cost at year

of

occurrence

($)

H.011678.6

(Alexandria)

4/8/2015

Saw Cutting Portland

Cement Concrete

Pavement

1

INLF

1.08

2037 2.36

H.011678.6

(Alexandria)

4/8/2015

Saw Cutting Portland

Cement Concrete

Pavement

1

INLF

1.08

2047 3.50

H.011678.6

(Alexandria)

4/8/2015

Full Depth Patching of

Jointed Concrete

Pavement (16.1 square

yards to 48.0 square

yards) (11" Thick)

643.03

Yd3

695.51

H.011678.6

(Alexandria)

8/12/2015

Cleaning and Sealing

Random cracks

29039.07

Mile 31408.65

2037 68820.23

H.010486.6

Full Depth Patching of

Jointed Concrete

425.16

1378.97

Table 113 (cont.)

235

Proposal

number and

district

Letting date

Item description

Price

at letting

date

($)

Unit

Net present

value, year

2017

($)

Year of

occurrence

Cost at year

of

occurrence

($)

(Alexandria) 9/10/2014

Pavement (16.1 square

yards to 48.0 square

yards) (10" Thick)

377.969

Yd3 2047

H.010486.6

(Alexandria)

9/10/2014

Full Depth Patching of

Jointed Concrete

Pavement (16.1 square

yards to 48.0 square

yards) (10" Thick)

377.969

Yd3

425.16

2037 931.58

H.010486.6

(Alexandria)

9/10/2014

Cleaning and Resealing

Existing Transverse

Pavements Joints

3643.08 Mile

4097.97

Net present value at 2017 32261.151

236

Add to that the maintenance and rehabilitation cost item. In this case, alternative 6 has

the lowest cost. The other option is to add the initial overall cost (including design and

overhead) to the maintenance and rehabilitation cost item. In this case, alternative 9 has the

lowest economic cost. Assignment of the economic score can be accomplished through

Equation 16:

For example, for alternative 6, the resulting score =

242231.77/(242231.77+267305.36+260277.49) = 0.314

In assigning an economic score in this study, there is an economic score of 0.5; the

final economic score after assigning the economic score may be calculated using Equation

17.

EconW× score for economic weight per alternative

Economic score for alternative 6 = 0.314× 0.5 = 0.157

Table 114. Cost analysis for alternatives (scenario 1)

Alternative Initial cost

(material)

Maintenance and

rehabilitation

item

Total

($/design)

Weighted Assigning

economic

score

6 228016.33 14215.44 242231.77 0.314 0.157

7 258131.70 9173.66 267305.36 0.347 0.173

9 228016.33 32261.15128 260277.49 0.338 0.169

Table 115. Cost analysis for alternatives (scenario 2)

Alternative Initial cost

(overall)

Maintenance

and

rehabilitation

item

Total

($/design)

Weighted Assigning

economic

score

6 825405.399 14215.44 839620.83 0.318 0.159

7 1203883.973 9173.66 1213057.63 0.460 0.230

9 549599.204 32261.15128 581860.35 0.220 0.110

5.3.1.10 Total sustainability score

The total score can then be calculated using Equation 18: overall final sustainability

score = weighted economic score for alternative + weighted environmental impact for

alternative. In the first scenario, considering only the material cost, alternatives 7 and 9 have

237

the lowest score. When the total initial cost is considered, alternative 9 has the lowest total

score as well, and is considered the best choice. The final values are illustrated in Table 116.

Table 116. Total score

Alternative Economic score Environmental

score

Total score

Scenario 1 Scenario 2 Scenario 1 Scenario 2

6 0.157 0.159 0.179 0.336 0.338

7 0.173 0.230 0.159 0.332 0.389

9 0.169 0.110 0.163 0.332 0.273

5.3.1.11 Statistical analysis

To be able to compare statistical significance of the results, another EPD will be used

to assess the environmental impact. Note that the economic impact cannot be compared

because cost data does not exist for states other than Louisiana. A compressive strength value

of 4400, 5000 and 6000 psi will be used to evaluate the following environmental

impact/inventory values: GWP, ODP, AP, EP , POCP, RE and NRE.

The scope will include the following stages: raw material extraction, transportation

from raw material extraction to manufacturing, manufacturing, and transportation from

manufacturing to project location. The total environmental score will be compared, since the

breakdown for EPD is not available for states other than Louisiana. The same procedure will

be followed to evaluate the total environmental impact with the same assumptions, only raw

data from EPD will change. The raw data used, extracted from EPD, for compressive strength

value of 4400 psi are illustrated in Table 117, as a sample.

Table 117. Total environmental impact per alternative

Alternative GWP

kg CO2

eq/ yd3

ODP

kg CFC-11 eq/

yd3

AP

kg SO2 eq/

yd3

EP

kg N eq/

yd3

POCP

kg O3 eq/

yd3

NRE

MJ/

yd3

RE

MJ/

yd3

6A 305.83 3.51E-06 1.69 0.05 24.31 1673.67 12.54

7B 262.25 3.07E-06 1.48 0.04 21.48 1488.64 10.77

9C 255.37 2.97E-06 1.44 0.04 21.25 1433.59 10.57

Average 274.48 3.18E-06 1.54 0.04 22.35 1531.97 11.29

238

Final results for the environmental score are illustrated in Table 118. To better

understand the data used, descriptive statistics is illustrated in Table 119, including the mean,

the standard deviation, and confidence interval. To evaluate results significance, analysis of

variance (ANOVA) is performed with a confidence interval of 95%. Results are illustrated in

Table 120. The resulting P value =0.999462 ( > 0.001 indicating insignificance of the

results).

Table 118. Environmental impact comparison

Alternative Environmental

score

(Louisiana)

Environmental

score

(4400 psi)

Environmental

score

(5000 psi)

Environmental

score

(6000 psi)

6 0.179 0.178 0.178 0.177

7 0.159 0.158 0.159 0.159

9 0.163 0.162 0.162 0.163

Mean 0.167 0.166 0.166 0.166

Standard

deviation 0.0106 0.0106 0.0102 0.0095

Table 119. Descriptive statistics for the environmental impact values

Criteria

Louisiana

data

4400

psi

5000

psi

6000

psi

Mean 0.167 0.166 0.166333 0.166333

Standard error 0.00611 0.00611 0.005897 0.005457

Median 0.163 0.162 0.162 0.163

Standard deviation 0.01058 0.010583 0.010214 0.009452

Sample variance 0.00011 0.000112 0.000104 8.93E-05

Skewness 1.45786 1.457863 1.565482 1.389636

Range 0.02 0.02 0.019 0.018

Minimum 0.159 0.158 0.159 0.159

Maximum 0.179 0.178 0.178 0.177

Sum 0.501 0.498 0.499 0.499

Count 3 3 3 3

Confidence level

(95.0%) 0.02629 0.02629 0.025374 0.023479

239

Table 120. Analysis of variance results

Source

of

Variation

SS df MS F P-value F critical

Between

Groups 1.58E-06 3 5.28E-07 0.005055 0.999462 4.066181

Within

Groups 0.000835 8 0.000104

Total 0.000837 11

5.3.1.12 Sensitivity analysis

Sensitivity analysis is an important criteria in decision making. Sensitivity analysis should

determine the sensitivity of an output to a change in input, while keeping all the other

alternatives constant. In this section, a sensitivity analysis will be performed to evaluate how

the change in the following criteria affects the total environmental impact for each alternative

1) Environmental impact of raw material extraction and manufacturing (reported from EPD)

2) Environmental impact of transportation

a) From raw material extraction to manufacturing (from EPD)

b) From manufacturing to project location

c) Total environmental impact of transportation from raw material extraction to

manufacturing and from manufacturing to project location

3) Impact of total distance traveled from raw material extraction to project location.

The sensitivity levels will be evaluated by an increase of 10% in the previous factors. Final

results are illustrated in Table 121.

240

Table 121. Sensitivity analysis and final environmental impact

Criteria Change on total

environmental impact (%)

Environmental impact of raw

material extraction and

manufacturing (reported from

EPD)

0.107

Environmental impact of

transportation (from raw material

extraction to manufacturing)

0.0259

Environmental impact of

transportation

(from manufacturing to project

location), by changing the

inventory values/environmental

impact of heavy duty truck

9.86

Total distance traveled from

manufacturing to project location

9.86

Environmental impact of total

transportation module

(transportation from raw material

extraction to manufacturing and

from manufacturing to project

location)

9.86

In a further interpretation for the results illustrated in Table 121, the final

environmental impacts are highly altered by changing criteria in the transportation module

either in changing the environmental impact of the transportation stage from manufacturing

to project location, or by changing the total distance traveled from manufacturing to project

location, or by changing the total environmental impact of transportation (transportation from

raw material extraction to manufacturing and from manufacturing to project location).

As for changing raw material extraction and manufacturing stages of concrete,

changing these criteria did not change the total environmental impact compared to the

transportation stages. This example illustrates the importance of the transportation module

and proves it to be a sensitive criteria towards the total environmental impact.

241

5.3.2 CASE STUDY 2: BENCHMARKING MODULE

The same case study will be performed using the benchmarking module for

illustration. A step by step procedure will be displayed. The same procedure and format will

be followed in this module.

5.3.2.1 Environmental performance

1. Select the state you want to use the mix design: The state is Louisiana.

2. The purpose of the design is benchmarking. The stakeholder is interested in

benchmarking the product, and wants to know whether the product is below or above the

market average.

3. Select the number of products to benchmark: The stakeholder might want to benchmark

the product with respect to various criteria, inclusive of a certain region, with respect to

the Hammond district or with respect to a specific parish. Also, the user might want to

measure the cost of the product to know whether the product is above or below the market

average.

4. Assign weights for the environmental and economic impacts. Both impacts will be

assigned a weight of 0.5

5. Convert the modulus of rupture to compressive strength value, using Equation 8, where:

MOR (psi) = 2.3 (fc)2/3 or fc= (MOR/2.3)3/2. This results in a compressive strength value

of (600/2.3)3/2 = 4213 psi

6. Select alternative mixes from the EPD data, to evaluate the environmental impact. The

user enters a specific, required mix design to seek the environmental impact in the

database. The stakeholder is interested in acquiring cement content around the 412 lb

value. This mix design is illustrated in Table 122.

242

Table 122. Required mix design

Cement

(lb)

Fly

ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate

2 (lb)

Mixing

water

(gallons)

Air

entertainer

(%)

412 102 1400 1600 1420 32 1

This exact mix design is not in the database and therefore, the stakeholder can select

from among the existing mixes. The nearest mixes based on the cement and fly ash amount

are illustrated in Table 123. As illustrated, there are various mix designs that appear. Yet

there should be some filtering criteria for the stakeholder. For example, one of the filtering

criteria could be the proximity to the project location. The user would select to benchmark the

product with respect to all the mixes produced in the Hammond area.

The environmental impact of the mixes 6, 7, and 9 are illustrated in Table 125. These

are the values extracted from EPD, with no modifications. Values of the environmental

impact will be averaged, and the design will proceed with the average value. This is one of

the differences between the alternative design module and the benchmarking module. As

illustrated, the values are given per 1 yd3. These are the impacts for A1: raw material

extraction and A3: manufacturing.

These values are given per 1 yd3. Some adjustments must be performed to adjust the

environmental impacts per the total design volume. The total design volume calculation is

illustrated in Table 126, for the 11 inch thickness. The calculation was performed using

Equation 6: This step remains intact, since the design will not change. Lv = LT×LW× LL

The total environmental impact for the design then should be adjusted according to

the overall design volume, using Equation 7.

Equation 7 Total environmental impact per design layer

243

Table 123. Corresponding mix designs

Alternative Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing water

(gallons)

Water

reducer

(oz)

District

Initial cost

($/yd3)

1 414 103 1,180.00 1,481.00 413 29.6 20.7 Baton Rouge 123

2 414 103 1,291.00 1,559.00 413 31 20.7 Baton Rouge 123

3 414 103 1,092.00 1,353.00 846 30.3 15.51 Baton Rouge 123

4 414 103 1,285.00 1,379.00 607 31 20.7 Baton Rouge 117

5 414 103 1,281.00 1,376.00 604 31 20.7 Baton Rouge 117

6 413 104 1,483.00 1,421.00 320 31 15.51 Hammond 106

7 414 103 1,399.00 1,652.00 0 30 20.68 Hammond 120

8 414 103 1,092.00 1,475.00 715 30.3 15.51 Hammond 123

9 414 103 1,362.00 1,682.00 0 30 20.68 Hammond 106

10 413 104 1,483.00 1,438.00 320 31 20.68 Hammond 220

11 414 103 1,000.00 1,483.00 550 29.7 30.2 Lafayette 116

12 414 103 1,521.00 1,521.00 0 29.5 31.2 New Orleans 106

Table 124. Filtering criteria based on manufacturer location

Alternative

Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Water

reducer

(oz)

District

Initial

cost

($/yd3)

6 413.66 103.33 0.00 1414.66 1585.00 106.66 30.33 Hammond 106

7 413.66 103.33 0.00 1414.66 1585.00 106.66 30.33 Hammond 120

9 413.66 103.33 0.00 1414.66 1585.00 106.66 30.33 Hammond 106

Average 413.66 103.33 0.00 1414.66 1585.00 106.66 30.33 Hammond 110.67

244

Table 125. Environmental impact extracted from EPD (Al and A3)

Alternativ

e

GWP

kg CO2

eq/yd3

ODP

kg CFC-11

eq/yd3

AP

kg SO2-

eq/yd3

EP

kg N

eq/yd3

POCP

kg O3

eq/yd3

NRE

MJ/

yd3

RE

MJ/

yd3

6 193.89 2.78E-06 0.801

0.0881

0 13.14 1400.76 157.49

7 194.07 2.77E-06 0.801

0.0880

4 13.13 1399.52 157.34

9 194.08 2.77E-06 0.801 0.09 13.13 1399.59 157.37

Average 194.02 2.77E-06 0.80 0.09 13.14 1399.96 157.40

Table 126. Final layer volume

Dimension Value Unit Unit conversion Final unit

Layer Thickness 11 Inch 1/36 Yd

Length 1 Mile 1760 Yd

Width 12 Feet 0.33 Yd

Total volume 2151.09 Yd3

For example, the total adjusted GWP for the average value is: The volume 2151.09

yd3×194.02 kg CO2 eq/yd3= 417347.167 kg CO2 eq. The environmental impact will be

adjusted accordingly to each alternative. Final results are indicated in Table 127.

Table 127. Adjusted environmental impact per volume

Alternative

GWP

kg CO2

eq

ODP

kg CFC-

11 eq

AP

kg SO2-

eq

EP

kg N

eq

POCP

kg O3 eq

NRE

MJ

RE

MJ

Average 417347.16 0.006 1724.17 189.43 28259.12 3011450.63 338584.14

As illustrated, the values have different units. Therefore, these should be normalized

to have consistent, unitless units, which can be summed up altogether in the end. The

normalization values used are illustrated in Table 128.

The normalization can be performed through dividing the environmental impact per

the normalization value. This can be accomplished by following Equation 2.

245

Table 128. Normalization values used

GWP (kg CO2eq/ yd3) 24000

ODP (kg CFC-11 eq/yd3) 0.160

AP (kg SO2-eq/yd3) 91

EP (kg N eq/yd3) 22

POCP (kg O3 eq/yd3) 1400

NRE (MJ/yd3) 288572.509

RE (MJ/yd3) 24874.54785

For example, the normalization value for the GWP for the average value is:

417347.167 kg CO2 eq/24000 kg CO2eq = 17.38. Normalized values are illustrated in Table

129.

Table 129. Normalized value for adjusted environmental impact per total volume

Alternative GWP ODP AP EP POCP NRE RE

Average 17.38 0.03 18.94 8.611 20.18 10.43 13.61

5.3.2.2 Transportation impact

Transportation from the raw material extraction to the manufacturing phase. These

are given per Athena Institute for each mix design. The values are given per 1 yd3. The values

are illustrated in Table 130. These values should be adjusted to total design volume. Since

this is the benchmarking module, the average value is computed to work in tandem with the

appropriate data.

Table 130. Transportation from raw material extraction to manufacturing (A2)

Alternative GWP

kg CO2

eq/ yd3

ODP

kg CFC-11

eq/yd3

AP

kg SO2

eq/yd3

EP

kg N eq/yd3

POCP

kg O3

eq/yd3

NRE

MJ/

yd3

RE

MJ/

yd3

6 24.484 9.31E-10 0.169 0.009 4.833 335.737 0.00

7 23.628 8.98E-10 0.164 0.009 4.681 323.994 0.00

9 23.53 8.95E-10 0.16 0.01 4.67 322.71 0.00

Average 23.883 9.08 E-10 0.166 0.009 4.833 327.481 0.00

The adjustment process is illustrated in Table 131, which is performed by multiplying

the average value in Table 130 by the total design volume. For example, the adjusted GWP

for the average alternative = 23.883 kg CO2 eq/ yd3×2151.09 yd3 = 51737.55 kg CO2 eq.

246

Table 131. Adjusted transportation impact per design volume

GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

51374.07 0.00 357.46 19.99 10396.84 704442.58 0.00

Part 2 Transportation impact from the raw material extraction to project location

To calculate the transportation impact from the raw material extraction to the use

phase, the distance between the manufacturers to the project location first should be

determined. This can be accomplished by calculating the distance between the two zip codes:

the zip code of the project location, as well as the manufacturer’s zip code. The zip code of

the project location is 70454 and the manufacturer zip codes are user input, as indicated in

Table 132. The user input value is one difference between the benchmarking module and the

alternative design comparison module. The distance can be calculated using Google maps.

The average transportation distance is 36.66 miles or 58.66 kms. The average distance will be

used.

Table 132. Total transportation distance (manufacturer to project location)

Alternative

number

Project

location

Manufacturer

location

Total distance

(miles)

Total distance

(km)

6 70454 70471 37.000 59.200

7 70454 70726 36.000 57.600

9 70454 70471 37.000 59.200

Average 36.66 58.66

Also, the total weight to be transported should be identified. The transportation will be

performed using a heavy duty truck with a weight of 80,000 lb and diesel fuel.

The total weight of concrete to be transported is illustrated in Table 133. These values

exist in the database (originally gathered from the manufacturer). As previously described,

the total weight to be transported is calculated by the vehicle weight and the total weight of

concrete to be transported. This can be accomplished through using Equation 9:

247

For example, the density for the average alternative = 3877.89 lb/yd3 and the total design

volume = 2151.09 yd3, therefore, the total average design weight =

3877.89 lb/yd3 × 2151.09 yd3 =8341712.04 lb. This weight value should be converted to

metric ton, which will be accomplished through multiplying the value by a factor of

0.00045359.

The average concrete weight to be transported = 8341712.04 lb × 0.00045359 =

3783.72 ton. The total weight to be transported for the average alternative is therefore the

sum of truck weight (800000 lb or 36.28 ton + 3783.72) = 3820 ton. To find the total number

of loads required, Equation 10 is used.

In this case, the average weight will be used = 8374663.14 lb/ 54000 lb = 154.48 loads

Table 133. Weight of concrete to transport

Alternative

number

Density

(lb/yd3)

Total weight

per design

volume of

concrete

(lb)

Weight

of

concrete

(ton)

Truck

weight

(ton)

Total

number

of loads

Total

weight

(truck+

concrete)

(ton)

Average 3877.89 8341712.04 3783.72 36.28 154.48 3820

To adjust the inventory values coming from the transportation module, Equation 11

should be used: Adjusted inventory values =

× total number of loads

The emissions/ inventory for the heavy duty truck is illustrated in Table 134

Table 134. Heavy duty truck emissions (kg/ton.km)

GWP

kg CO2

eq

ODP

kg CFC-

11 eq

AP

kg SO2

eq

EP

kg N eq

POCP

kg O3 eq

NRE

MJ

RE

MJ

3.24E-01 0.00E+00 1.34E-03 5.55E-04 4.62E-02 8.09E-02 0.00

248

For example, to calculate the transportation impact from the manufacturing to the

project location for GWP: Adjusted inventory values = 2 × 0.324 kg CO2/ton.km (3820 ton)

×58.66 km ×154.48 =22433226.08 kg CO2 eq. Values are illustrated in Table 135.

Table 135. Transportation impact from the manufacturer to project location

Alternative

GWP

kg CO2

eq

ODP

kg CFC-

11 eq

AP

kg SO2 eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

Average 22433226.08 0.00 92779.391 38427.28 3198811.86 5601382.68 0.00

Total transportation impact: The total transportation impact is the sum of Part 1

(transportation from raw material extraction to manufacturing) and Part 2 (transportation

from the manufacturer to project location). For GWP, both values will lead to

51374.07+22433226.08= 22484600.16 kg CO2 eq. Values are illustrated in Table 136. These

values should be added and then normalized.

Table 136. Total transportation impact per alternative

Alternative GWP

kg CO2 eq

ODP

kg CFC-11 eq

AP

kg SO2 eq

EP

kg N eq

POCP

kg O3 eq

NRE

MJ

RE

MJ

Average 22484600.16 0.00 93136.85 38447.28 3209208.70 6305825.27 0.00

To normalize the total transportation impact values, each environmental impact

should be divided by the corresponding normalization value. For example, the average mix

design will have the following value after normalization (for GWP) = 22484600.16 kg CO2

eq/ 24000 kg CO2 eq = 936.85. The total transportation values are illustrated in Table 137 for

the average.

Table 137. Total normalized transportation impact per alternative

Alternative GWP ODP AP EP POCP NRE RE

Average 936.85 0.00 1023.48 1747.60 2292.29 21.85 0.00

249

5.3.2.3 Total environmental impact

The total environmental impact presents the total of the environmental impact coming

from concrete design (EPD), as well as the total transportation impact (from raw material

extraction to manufacturing and from manufacturing to project location). This results from

the values displayed in Table 138. Based on design volume, the environmental impact

extracted from EPD and adjusted, was previously described:

Environmental impact from EPD (adjusted per volume) + total transportation impact

= 417347.16 kg CO2 eq + 22484600.16 kg CO2 eq =22901947.33 kg CO2. These total

environmental impacts must be normalized. Values after normalization are illustrated in

Table 139.

Table 138. Total environmental impact per alternative

Alternative GWP

kg CO2 eq

ODP

kg CFC-11 eq

AP

kg SO2 eq

EP

kg N eq

POCP

kg O3 eq

NRE

MJ

RE

MJ

Average 22901947.33 0.006 94861.03 38636.71 3237467.83 9317275.90 338584.14

Table 139. Normalization values for the total environmental impacts

Alternative GWP ODP AP EP POCP NRE RE

Average 954.248 0.037 1042.429 1756.214 2312.477 32.287 13.612

5.3.2.4 Weighing the environmental impact

Based on stakeholder preference, weighting can be assigned to the average

environmental impacts. The weighting procedure will be used here for demonstration. The

weights used are illustrated in Table 140.

Table 140. Weights used in the study

GWP ODP AP EP POCP NRE RE Total

0.200 0.150 0.150 0.150 0.150 0.100 0.100 1

The total environmental impact after the weighting process is illustrated in Table 130.

Equation 3 can be used to convert the environmental impacts into weighted environmental

impacts: weighted impact = assigned weight × normalized value

250

For example, for the weighted alternative = 0.20×954.248= 190.85. At this point in time, the

values are on the same scale due to normalization, which placed all the values on the same

scale, as well as unitless).

The sum of all the environmental values together is the total environmental score for

the average impact. GWP+ODP+AP+POCP+NRE-RE = 959.391. Here the relative score no

longer exists, since the average value is taken. Values are illustrated in Table 141.

Table 141. Total environmental impact after normalization and weighting

Alternative GWP ODP AP EP POCP NRE RE Total

Average 190.850 0.006 156.364 263.432 346.872 3.229 1.361 959.391

5.3.2.5 Economic impact

As previously described, the economic analysis will be accomplished though

performing a complete lifecycle cost analysis for each alternative. This lifecycle cost analysis

consists of an initial cost (occurring at the present) and a maintenance and rehabilitation cost

(occurring in the future). The initial cost for the selected mix designs is extracted from the

database. These values include the profits, overheads, installation fees, etc. The initial cost

items of the selected alternatives (6, 7, and 9) are illustrated in Table 142. The letting date is

provided, which can be used to calculate the net present value or the average price at the

same point in time/at present as the year 2017. An analysis period of 50 years is used, with a

discount rate of 4%. The calculation will be the same as the alternative design module, except

for the fact that the values will be averaged to have a single number with which to deal.

The initial cost items are illustrated in Table 142. This is for the materials cost only;

the average value is taken. The average value is 110.67 $/yd3 to be adjusted to total volume =

110.67 $/yd3× 2151.09 yd3 = $238061.96 The overall initial cost is illustrated in Table 143.

This includes the overheads, profits, etc. and the cost is adjusted to volume.

Table 142. Average material price

Alternative Initial cost ($/yd3)

251

6 106

7 120

9 106

Average 110.67

Adjusted per volume 238061.96

Table 143. Cost analysis for alternatives (scenario 2)

Alternative

number

Bid unit price discounted to

current year (2017) and

adjusted per total design

volume ($/design)

6 825405.399

7 1203883.97

9 549599.204

Average 859629.52

The average maintenance and rehabilitation item for the average alternative is

illustrated in Table 144, under the same assumptions previously illustrated in the alternative

design module. The average value is taken as well, but in this case the average value is per

each item and not for the overall design. As for the maintenance and rehabilitation items, the

benchmark is taken per activity; as illustrated in Table 144.

Table 144. Average maintenance and rehabilitation activities

Item Design 6 ($) Design 7 ($) Design 9 ($) Average ($)

Full Depth Patching of

Jointed Concrete Pavement

(16.1 square yards to 48.0

square yards) (10" Thick)

425.1645

445.4105112

425.164 431.9/Yd3

Cleaning and Sealing

Random cracks

13362.95 8280.46 31408.658 17684.022//Mile

Saw Cutting Portland

Cement Concrete

Pavement

1.08 1.19

1.0816

1.116/ INLF

5.3.3 CASE STUDY 3 ALTERNATIVE DESIGN COMPARAISION

5.3.3.1 Project description

This project falls under a proposal number of H.003495. The project is titled I-49N,

segment K - phase 2 -220 to Martin Luther King Drive. The project is in Caddo Parish,

Shreveport district, with a zip code of 71107.

252

5.3.3.2 Design inputs

The project traffic information is illustrated in Table 145. The project is divided into two

roads; each road has certain characteristics, such as directional distribution, K value, truck

distribution, design speed, and average daily traffic.

Table 145. Project traffic data (LaDOTD)

Criteria I 49 Traffic data MLK drive

D (Directional distribution) 55.3% 7%

K 10.6% 11%

T (truck distribution) 14.7% 9.3%

Design speed (MPH) 60 40

2013 Average Daily Traffic (A.D.T.) 22869 6349

2032 A.D.T 33165 7388

5.3.3.3 Design properties

The design is illustrated in Figure 52. The layer inputs are as follows: PCC layer, class 2

Base course (recycled PCC or stone), subgrade layer (treated). Thicknesses are illustrated in

Figure 52. The Modulus of rupture is 600 psi, resulting in a compressive strength value of

4213 psi

Figure 48. Design layers

Portland

cement

concrete

11 inch

Class 2 Base

Course

4 inch

Subgrade layer

(treated)

12 inch

253

5.3.3.4 Environmental impact

To evaluate the environmental impact of this project, the developed framework will be

used. The solution will be provided in steps for replication.

1. Select the state you want to use the mix design: The state is Louisiana.

2. The purpose of the design is alternative design comparison. The stakeholder is interested

in evaluating the environmental impact of various alternatives. These different

alternatives are various mix designs, since the design cannot be changed.

3. Select the number of designs to evaluate: only one design.

4. Select the number of mixes to evaluate: 3 PCC mix designs

5. Assign weights for the environmental and economic impacts. Both impacts will be

assigned a weight of 0.5

6. Convert the modulus of rupture to compressive strength value using Equation 8, where:

MOR (psi) = 2.3 (fc)2/3 or fc= (MOR/2.3)3/2. This results in a compressive strength value

of (600/2.3)3/2 = 4213 psi

7. Select alternative mixes from the EPD data to evaluate the environmental impact. The

user enters a specific mix design (required by the design) to look for an environmental

impact in the database. This mix design is illustrated in Table 146. Normally, the paving

mix designs have a cement content ranging from 400 to 550 lbs. The input value for the

cement content should be in this range.

Table 146. Required mix design

Cement

(lb)

Fly

ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate

1 (lb)

Coarse

aggregate

2 (lb)

Mixing

water

(gallons)

Air

entertainer

(%)

500 100 1501 1520 750 29 3

This exact mix design is not in the database; therefore, the stakeholder can select from

among the existing mixes. As illustrated in Table 147, there are various mix designs that

appear. There should be some filtering criteria for the stakeholder. For example, one of the

254

filtering criteria can be proximity to project location (and thereby provides less environmental

impact for transportation). The mixes selected are the mixes manufactured in the Shreveport

district.

For example, this project is in Shreveport and therefore, the manufacturers located in

Shreveport can be the best alternatives. This narrows the choice of mixes to options 5, 6, and

7. The new selections are illustrated in Table 148.

The environmental impact of the mixes 5, 6 and 7 are illustrated in Table 149. These

are the values extracted from EPD, with no modifications. As illustrated, the values are given

per 1 yd3. These are the impacts for A1: raw material extraction and A3: manufacturing.

These values are given per 1 yd3, yet some adjustments must be performed to adjust

the environmental impacts per the total design volume. The total design volume calculation is

illustrated in Table 150, for an 11 inch thickness. The calculation was performed using

Equation 6: Lv = LT×LW× LL

To get the total environmental impact per total design volume, Equation 7 is used:

For example, the total adjusted GWP, for alternative 5 = the volume 2151.09

yd3×235.88 kg CO2 eq/yd3= 507413.993 kg CO2 eq. The environmental impact will be

adjusted accordingly for each alternative. Final results are indicated in Table 144. As

illustrated, the values have different units. Therefore, these should be normalized to have

consistent, unitless units that can be summed up altogether in the end. The normalization

values used are illustrated in Table 152 .

The normalization can be performed through dividing the environmental impact per the

normalization value. This can be accomplished by following Equation 2.

For example, the normalization value for the GWP for alternative 5 =

255

507413.993kg CO2 eq/24000 kg CO2eq = 21.14. All normalized values are illustrated in

Table 152.

5.3.3.5 Transportation module

Transportation from the raw material extraction to the manufacturing phase. These are

given per Athena Institute for each mix design. The values are given per 1 yd3. The values are

illustrated in Table 153. These values should be adjusted to total design volume.

The adjustment process is illustrated in Table 148, which is performed by multiplying

the values in Table 153 by the total design volume. For example, the adjusted GWP for

alternative 5 = 23.040kg CO2 eq/yd3×2151.09 yd3= 49562.32 CO2 eq.

Part 2. Transportation impact from the raw material extraction to project location

To calculate the transportation impact from the raw material extraction to the project

location, the distance between the manufacturers to project location first should be

determined.

256

Table 147. Corresponding mix design

Alternative Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Water

reducer

(oz)

District

Initial

cost

($/yd3)

1 517 0 1,235.00 1,332.00 450 30.9 23.23 Hammond 112

2 510 0 1,052.00 1,638.00 402 28.1 30.8 Lafayette 116

3 517 0 1,006.00 1,488.00 555 29.4 2.5 Lafayette 116

5 508 0 737 1,698.00 752 29.5 30.5 Shreveport 119

6 508 0 1,737.00 1,698.00 752 29.2 20.3 Shreveport 119

7 508 0 730 1,698.00 752 29.2 20.3 Shreveport 123

Table 148. Filtering criteria based on manufacturer location

Alternative

Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Water

reducer

(oz)

Initial cost

($/yd3)

5 508 0 737 1,698.00 752 29.5 30.5 119

6 508 0 1,737.00 1,698.00 752 29.2 20.3 119

7 508 0 730 1,698.00 752 29.2 20.3 123

Table 149. Environmental impact extracted from EPD (Al and A3)

Alternative

GWP

kg CO2

eq/yd3

ODP

kg CFC-11

eq/yd3

AP

kg SO2

eq/yd3

EP

kg N

eq/yd3

POCP

kg O3

eq/yd3

NRE

MJ/yd3

RE

MJ/yd3

5 235.88 0.00 0.96 0.106 15.94 1681.57 190.54

6 237.33 0.00 0.97 0.107 16.18 1705.44 192.74

7 235.79 0.00 0.96 0.106 15.93 1679.69 190.53

257

Table 150. Adjusted environmental impact per volume

Alternative GWP

kg CO2

eq

ODP

kg CFC-

11 eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3 eq

NRE

MJ

RE

MJ

5 507413.99 0.007 2081.93 228.17 34300.04 3617239.26 409886.74

6 510531.18 0.007 2106.08 230.99 34807.80 3668574.88 414619.55

7 507207.73 0.007 2080.78 228.12 34285.62 3613183.16 409853.61

Table 151. Normalization values used

GWP (kg CO2eq/ yd3) 24000

ODP (kg CFC-11 eq/yd3) 0.160

AP (kg SO2 eq/yd3) 91

EP (kg N eq/yd3) 22

POCP (kg O3 eq/yd3) 1400

NRE (MJ/yd3) 288572.509

RE (MJ/yd3) 24874.54785

Table 152. Normalized value for adjusted environmental impact per total volume

Alternative GWP ODP AP EP POCP NRE RE

5 21.14 0.043 22.87 10.37 24.50 12.53 16.47

6 21.27 0.045 23.14 10.50 24.86 12.71 16.66

7 21.13 0.043 22.86 10.36 24.49 12.52 16.47

Table 153. Transportation from raw material extraction to project location (A2)

Alternative

GWP

kg CO2

eq/ yd3

ODP

kg CFC-11

eq/yd3

AP

kg SO2

eq/yd3

EP

kg N

eq/yd3

POCP

kg O3

eq/yd3

NRE

MJ/

yd3

RE

MJ/

yd3

5 23.04 0.00 0.16 0.009 4.64 315.90 0.00

6 28.94 0.00 0.20 0.011 5.69 396.93 0.00

7 22.98 0.00 0.16 0.009 4.63 315.10 0.00

Table 154. Adjusted transportation impact per design volume

Alternative GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

5 49562.32 0.00 350.76 19.60 9985.03 679548.35 0.00

6 62271.30 0.00 431.08 24.08 12240.80 853839.53 0.00

7 49436.33 0.00 349.96 19.55 9962.74 677820.48 0.00

258

This can be accomplished by calculating the distance between the two zip codes of the

project location, as well as the manufacturer location. The zip code of the project location is

71107, and the manufacturer zip codes are presented in the EPD for each mix design. Table

155 illustrates the project zip code, the manufacturer zip code, and the distance between the

project and the manufacturer location (calculated through Google maps). Results in Table

155 indicate that the transportation values are almost the same, since the manufacturer is in

the Shreveport area for all alternatives.

Table 155. Total transportation distance (manufacturer to project location)

Alternative

number

Project

location

Manufacturer

location

Total distance

(miles)

Total distance

(km)

5 71107 71108 13 20.80

6 71107 71111 14 22.40

7 71107 71111 14 22.40

Moreover, the type of truck used to transport concrete must be identified, as well as

the total weight to be transported. The transportation will be performed using a heavy duty

truck with a weight of 80,000 lb and diesel fuel.

As previously described, the total weight to be transported combines the vehicle

weight and the total weight of concrete to be transported. To get the total design weight for

concrete, Equation 9 should be used. This can be accomplished through using Equation 9:

M = D ×Lv

For example, the density for alternative 5 = 4000.819 lb/yd3 and the total design

volume = 2151.09 yd3; therefore, the total design weight = 4000.819 lb/yd3×2151.09 yd3 =

8606152.733 lb. Then this weight value should be converted to metric ton, which will be

accomplished through multiplying the value by 0.00045359. Adjusted weight = 8606152.733

lb × 0.00045359 = 3903.66 ton

259

The total weight to be transported for each alternative is therefore the sum of the truck

weight, as well as of the concrete transported. Final values are illustrated in Table 156. To get

the total number of loads required, Equation 10 should be used.

For example, for alternative 5, the total number of loads = 8606152.73 lb/54000 lb = 159.37

loads. For example, to calculate the transportation impact from the manufacturing to the

project location for GWP, use alternative 5:

Adjusted inventory values = 2 × 0.324 kg CO2/ton.km ×3939.95 ton × 20.8 km

×159.37 = 8463394.48 kg CO2 eq. All values are illustrated in Table 158.

Table 156. Weight of concrete to transport

Alternative

number

Density

(lb/yd3)

Total weight per

design volume of

concrete

(lb)

Total weight

per design

volume of

concrete

(ton)

Total

number

of loads

Total weight

(truck+

concrete)

(ton)

5 4000.81 8606152.73 3903.66 159.37 3939.95

6 3819.91 8217016.49 3727.15 152.16 3763.44

7 3812.92 8201966.88 3720.33 151.888 3756.61

Table 157. Heavy duty truck emissions

Global

Warming

Air kg CO2

eq

Ozone Depletion

Air kg CFC-11 eq

Acidification

Air

kg SO2 eq

Eutrophication

Water

kg N eq

Smog

Air

kg O3 eq

Fossil Fuel

Depletion

MJ

3.24E-01 0.00E+00 1.34E-03 5.55E-04 4.62E-02 8.09E-02

Table 158. Transportation impact from the manufacturer to project location

Alternative GWP

kg CO2

eq

ODP

kg

CFC-11

eq

AP

kg SO2 eq

EP

kg N eq

POCP

kg O3 eq

NRE

MJ

RE

MJ

5 8463394.48 0.00 35002.92 14497.48 1206817.36 2113236.46 0.00

6 8312446.63 0.00 34378.63 14238.91 1185293.31 2075546.08 0.00

7 8282172.25 0.00 34253.42 14187.05 1180976.41 2067986.83 0.00

Total transportation impact. The total transportation impact is the sum of Part 1

(transportation from raw material extraction to manufacturing) and Part 2 (transportation

260

from the manufacturer to project location). Values are illustrated in Table 159. These values

should be normalized.

Table 159. Total transportation impact per alternative

Alternative

GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

5 8512956.80 0.00 35353.68 14517.08 1216802.40 2792784.81 0.00

6 8374717.94 0.00 34809.72 14263.00 1197534.11 2929385.62 0.00

7 8331608.58 0.00 34603.39 14206.61 1190939.16 2745807.32 0.00

To normalize the total transportation impact values, each value should be divided by

the corresponding normalization value. For example, alternative 5 will have the following

value after normalization (for GWP) = 8512956.80 kg CO2 eq/ 24000 kg CO2 eq = 354.707

The total transportation values are illustrated in Table 160 for the three alternatives.

Table 160. Normalized total transportation impact per alternative

Alternative

GWP

kg CO2

eq

ODP

kg CFC-

11 eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

5 354.707 0.00 388.502 659.867 869.14 9.67 0.00

6 348.947 0.00 382.524 648.318 855.38 10.15 0.00

7 347.150 0.00 380.257 645.755 850.67 9.51 0.00

5.3.3.6 Total environmental impact

The total environmental impact is the sum of the environmental impact coming from

concrete design (EPD), as well as the total transportation impact (from raw material

extraction to manufacturing and from manufacturing to project location). This will result

from the values given in Table 161. For example, the environmental impact extracted from

EPD and adjusted as based on design volume was previously described:

Environmental impact from EPD (adjusted per volume) + total transportation impact

= 507413.99 kg CO2 eq + 8512956.80 kg CO2 eq =9020370.80 kg CO2 eq

261

Table 161. Total environmental impact per alternative

Alternative

GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

5 9020370.80 0.007 37435.62 14745.25 1251102.44 6410024.08 409886.74

6 8885249.12 0.007 36915.80 14493.99 1232341.92 6597960.51 414619.55

7 8838816.32 0.007 36684.18 14434.73 1225224.78 6358990.49 409853.61

These total environmental impacts need to be normalized. Values after normalization

are illustrated in Table 162.

Table 162. Normalization values for the total environmental impacts

Alternative GWP ODP AP EP POCP NRE RE

5 375.84 0.043 411.38 670.23 893.64 22.21 16.47

6 370.21 0.045 405.66 658.81 880.24 22.86 16.66

7 368.28 0.043 403.12 656.12 875.16 22.03 16.47

5.3.3.7 Weighing the environmental impact

Based on stakeholder preference, weighting can be assigned to the impacts. The weighting

procedure will be used here for demonstration. Default weights were used for this case. The

weights are illustrated in Table 163.

Table 163. Weights used in the study

GWP ODP AP EP POCP NRE RE Total

0.200 0.150 0.150 0.150 0.150 0.100 0.100 1

The total environmental impact after the weighting process is illustrated in Table 164.

Equation 3 can be used to convert the environmental impacts into weighted environmental

impacts:

For example, for alternative 5 = 375.84× 0.200 = 75.17

At this point in time, the values are on the same scale due to normalization, which places all

the values on the same scale, as well as unitless). The sum of all the environmental values

262

together is the environmental score per alternative, and then the RE value is deducted =

GWP+ODP+AP+POCP+NRE-RE

The relative score is the environmental impact score compared for each alternative,

with respect to the other alternatives. This can be accomplished through Equation 14.

Score for environmental impact for each alternative =

Total environmental score for Alternative i/ ∑Environmental impact for all

alternatives.

For example, the score for alternative 5 = score for environmental impact for

alternative 5/ sum of all scores = 372.03/ (372.03+366.38+364.38) = 0.337

This equation was repeated for all other alternatives. Values are illustrated in Table

165. The alternative having the lowest score is the one that has the lowest environmental

impact, which is alternative 7 in this case. When the stakeholder assigned a weight for the

environmental score (which is the case, since the assigned weight is 0.5), then the final

environmental score after adjusting the weight may be calculated using Equation 15.

When the stakeholder assigned a weight for the environmental score (which is the

case , since the assigned weight is 0.5), then the final environmental score after adjusting the

weight may be calculated using Equation 15.

Weighted environmental score per alternative

for an alternative.

For example, for alternative 5, the weighted score = 0.5 × 0.337= 0.169

Table 164. Total environmental impact after normalizing and weighting

Alternative GWP ODP AP EP POCP NRE RE Total

5 75.17 0.007 61.70 100.53 134.04 2.22 1.64 372.03

6 74.04 0.007 60.85 98.82 132.03 2.28 1.66 366.38

7 73.65 0.007 60.46 98.41 131.27 2.20 1.64 364.38

263

Table 165. Relative score and environmental score

Alternative Relative

score

Assigning

environmental

score

5 0.337 0.169

6 0.332 0.166

7 0.330 0.165

5.3.3.8 Economic impact

As previously described, the economic analysis will be accomplished through

performing a complete lifecycle cost analysis for each alternative. This lifecycle cost analysis

consists of an initial present cost, and a maintenance and rehabilitation cost occurring in the

future.

The maintenance and rehabilitations schedule is performed based on the Louisiana

Department of Transportation and Development schedule, previously described in the

literature review. This is indicated in Table 166. The analysis period is 50 years. The initial

cost will start at year 0, then there will be a maintenance and rehabilitation cost at years 20

and 30 from the start date of the project.

Table 166. Lifecycle cost analysis based on the State of Louisiana

The initial cost for the selected mix designs is extracted from the database. These values

include the profits, overheads, installation fees, etc. Notably, the initial cost exists for all the

mix designs. However, there could be a problem associated with the maintenance and

rehabilitation, since the mixes have been used for the past five years and therefore, these

Project Type Alternate Year 0 Year 15 Year 20 Year 30 Year 50

Interstate

New

Construction

Rigid New JPC

Pavement

No

Action

Clean/Seal

Joints

Patch 1%

of Joints

Retexture

Patch 3%

of Joints

End of

life

No

salvage

value.

264

mixes would not have maintenance and rehabilitation items associated with them. As for the

initial cost items, the values are illustrated in Table 167. The letting date is provided, which

can be used to calculate the net present value for this mix design, as well as to compare all

mixes at the same point in time, such as the current year, 2017. This can be accomplished by

using the net present value equation (Equation 4). For example, for alternative 5, the total

price year 2017= 201.60 (1+ 0.04)5 = $245.277 .A discount rate of 4% was used. All the

values are illustrated in Table 168. To find the total cost per design volume, the cost should

be adjusted per total volume = $245.277 × 2151.097 yd3 = $527615.236. The adjusted cost

per total design volume is illustrated in Table 168.

As for the maintenance and rehabilitation items, the compressive strength value of the

mix designs will be matched to the compressive strength value and /or mix design breakdown

of older projects which have maintenance and rehabilitation activities, with an assumption

that the newer projects will undergo the same maintenance and rehabilitation activities.

The process of selecting activities also will be illustrated. For example, the same item

might occur in different districts, and therefore the unit price will vary. The perfect case

would be to select the maintenance and rehabilitation activities that occurred in the same

district. In the event there are no maintenance and rehabilitation activities that occurred in the

same district, the user might select the lowest maintenance and rehabilitation activity from

other districts

For alternative 5, the matched projects with associated compressive strength value is

illustrated in Table 169. Should the projects have associated mix design breakdowns, these

are also illustrated in Table 169, should the user select maintenance and rehabilitation items

based on both the compressive strength value and the mix design breakdown. As illustrated in

Table 170, the closest mix design breakdown is that of project 195-03-0029 (showing a

tolerance up to 10%).

265

Table 167. Initial cost (bid price for each alternative)

Alternative

number

Letting

Date

Parish

name Item Description

Bid unit

price per

(yd3)

Compressive

strength value

(psi)

5 11/14/2012 Caddo Portland Cement Concrete Pavement (10" Thick) $201.60 5383

6 5/14/2014 Caddo Portland Cement Concrete Pavement (9" Thick) $280.00 5043

7 6/11/2014 Webster Portland Cement Concrete Pavement (13" Thick) $221.54 4730

Table 168. Initial cost items per alternative

Alternative

number

Letting

date

Parish

name

Item description

Bid unit price

at letting date

(yd3)

Bid unit price

at current year,

2017

($/yd3)

Bid unit price

adjusted per total

design volume

at current year,

2017

($/design)

5 11/14/2012 Caddo Portland Cement Concrete

Pavement (10" Thick) $201.60 245.277 527615.236

6 5/14/2014 Caddo Portland Cement Concrete

Pavement (9" Thick) $280.00 314.961 677513.812

7 6/11/2014 Webster Portland Cement Concrete

Pavement (13" Thick) $221.54 249.200 536058.607

266

Depending on data availability, the maintenance and rehabilitation items are

illustrated in Table 171. However, Projects 451-01-0108, 195-03-0029, and 455-09-0024, did

not show any maintenance and rehabilitation activities (all the items shown were related to

initial cost items for rigid pavements). Therefore, the user should select maintenance and

rehabilitation activities from other projects, with available maintenance and rehabilitation

items.

Table 169. Projects associated with the selected compressive strength value alternative 5

Compressive

strength value

(psi)

Project ID Mix design

available?

5383 H.000792.6 No

5383 H.010351.6 No

5283 H.010487.6 No

5700 195-03-0029 Yes

5500 020-08-0015 Yes

5620.51 455-09-0024 Yes

Table 170. Matching compressive strength value alternative 5

Proposal ID

Compressive

strength

value (psi)

Cement

(lb)

Fly

ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate

1 (lb)

Coarse

aggregate

2 (lb)

Mixing

water

(gallons)

Air

entertainer

(%)

195-03-0029 5700 436 109 1097 404 1293 34.6 4

455-09-0024 5620.51 420 109 1437 1300 415 26 1.5

020-08-0015 5500 508 0 1397 1750 0 29 1.5

As illustrated in Table 171, none of the maintenance and rehabilitation options

occurred in the Shreveport district. Therefore, the user has an option to select the

maintenance and rehabilitation items from any other district. One option is to select the

lowest maintenance and rehabilitation items. For example, there are three costs for the saw

cutting which occur in three different districts. Since none of them is in the Shreveport

district, the user can select the lowest cost based on net present value at year 2017. In this

instance, the maintenance and rehabilitation item occurring in Hammond district, is the

lowest in cost and the one selected.

267

In alternative 6, there are only projects that matched the compressive strength

values and none matched the mix design breakdown. Therefore, these will be the items from

which to select the maintenance and rehabilitation activities. Associated projects are

illustrated in Table 171. As illustrated in Table 171, should there be the same maintenance

and rehabilitation activities in various districts, the user can select the lower item. Selected

items by the user will have the year of occurrence next to them.

In alternative 7, only projects that matched the compressive strength values are

shown; none matched the mix design breakdown. Therefore, these will be the items from

which to select the maintenance and rehabilitation activities. Associated projects are

illustrated in Table 174.

The maintenance and rehabilitation items associated with Shreveport district are first

to be selected. The remainder is selected from other districts, as illustrated in Table 175.

5.3.3.9 Final weight for the economic impact

The economic impact will be performed using initial cost and maintenance and rehabilitation

cost. Values for each alternative are illustrated in Tables 176 and 177. There are two

scenarios here. The first scenario is to calculate the total cost with respect to the initial cost,

pertaining to the material only, and then add the maintenance and rehabilitation cost item. In

this case, alternative 7 has the lowest cost. To assign the economic score, this can be

accomplished through Equation 16.

Score for economic impact for alternative = net present value for this alternative/net

present value for all alternatives or =

For example, for alternative 5, the resulting score

260931.07/(260931.07+263839.20+453914.01) = 0.266

268

Table 171. Maintenance and rehabilitation activities for matching projects alternative 5

Proposal

number and

district

Letting date

Item description

Price

at letting date

per unit

Unit

Net present

value ($)

(2017)

Year of

occurrence

Cost at year

of occurrence

($)

H.000792.6

(Alexandria) 6/24/2015

Saw Cutting Portland

Cement Concrete

Pavement

5 INLF 5.408

H.010351.6

(Lafayette) 10/8/2014

Saw Cutting Portland

Cement Concrete

Pavement

1 INLF

1.12

H.010487.6

(Alexandria)

9/10/2014

Cleaning and Sealing

Random cracks

3643.08

Mile

4097.97

2037

8979.16

H.010487.6

(Alexandria)

9/10/2014

Full Depth Patching of

Jointed Concrete Pavement

(16.1 square yards to 48.0

square yards) (10" Thick)

377.96

Yd3

425.16

2047

1378.97

H.010487.6

(Alexandria)

9/10/2014

Full Depth Patching of

Jointed Concrete Pavement

(16.1 square yards to 48.0

square yards) (10" Thick)

377.96

Yd3

425.16

2037 931.58

020-08-0015

(Hammond)

4/8/2015

Saw Cutting Portland

Cement Concrete

Pavement

1

INLF

1.08 2037 2.36

020-08-0015

(Hammond)

4/8/2015

Saw Cutting Portland

Cement Concrete

Pavement

1

INLF

1.08 2047 3.50

Net present value at 2017 for selected items 4950.465

269

Table 172. Projects associated with the selected compressive strength value alternative 6

Compressive

strength value

(psi)

Project ID

Mix design

available?

5043 H.010360.6 No

5300 H.012094.6 No

5500 H.009598.6 No

Table 173. Maintenance and rehabilitation items for alternative 6

Proposal

number and

district

Letting date

Item description

Price

at letting

date per unit

Unit

Net present

value ($)

(2017)

Year of

occurrence

Cost at year

of

occurrence

($)

H.010360.6

(Alexandria)

2/25/2015

Cleaning and Sealing

Random Cracks.

6335.79

Mile

6852.79

2037

15015.32

H.010360.6

(Alexandria)

2/25/2015

Full Depth Patching of

Jointed Concrete

Pavement (16.1 square

yards to 48.0 square

yards) (10" Thick)

464.36

Yd3

502.25

2047

1629.01

H.010360.6

(Alexandria)

2/25/2015

Full Depth Patching of

Jointed Concrete

Pavement (16.1 square

yards to 48.0 square

yards) (10" Thick)

464.36

Yd3

502.25 2037 1190.30

H.010360.6

(Alexandria)

2/25/2015

Saw Cutting Portland

Cement Concrete

Pavement

0.6 INLF

0.64 2037 1.42

H.010360.6 2/25/2015 Saw Cutting Portland 0.6 INLF 0.64 2047 2.10

Table 173 (cont.)

270

Proposal

number and

district

Letting date

Item description

Price

at letting

date per unit

Unit

Net present

value ($)

(2017)

Year of

occurrence

Cost at year

of

occurrence

($)

(Alexandria) Cement Concrete

Pavement

H.012094.6

(Hammond) 6/22/2016

Full Depth Patching of

Jointed Concrete

Pavement (16.1 square

yards to 48.0 square

yards) (10" Thick)

3522.51 Yd3 3663.4

H.009598.6

(Baton Rouge)

5/27/2015

Full Depth Patching of

Jointed Concrete

Pavement (16.1 square

yards to 48.0 square

yards) (9" Thick)

1257.83 Yd3

1360.47

H.009598.6

(Baton Rouge)

5/27/2015

Full Depth Patching of

Jointed Concrete

Pavement (16.1 square

yards to 48.0 square

yards) (12" Thick)

486.20 Yd3

525.87

Net present value at 2017 for selected items 7858.60

271

Table 174. Projects associated with the selected compressive strength value alternative 7

Compressive

strength value

(psi)

Project ID

Mix design

available?

4730 H.001263.6-R1 No

5100 H.009539.6 No

4900 H.009574.6 No

5150 H.003200.6 No

Table 175. Maintenance and rehabilitation activities for alternative 7

Proposal number

and district

Letting date

Item description

Price

at letting date

per unit

Unit

Net present

value ($)

(2017)

Year of

occurrence

Cost at year

of occurrence

($)

H.001263.6-R1

(Alexandria)

7/24/2013

Cleaning and Sealing

Random Cracks

160934.44

Mile

188270.54

2037

412523.94

H.009539.6

(Alexandria)

3/12/2014

Full Depth Patching of

Jointed Concrete Pavement

(16.1 square yards to 48.0

square yards) (10" Thick)

395.96

Yd3

445.41

975.94

H.009539.6

(Alexandria)

3/12/2014

Full Depth Patching of

Jointed Concrete Pavement

(16.1 square yards to 48.0

square yards) (10" Thick)

395.96

Yd3

445.41

1444.64

H.009574.6

(Shreveport)

5/14/2014

Full Depth Patching of

Jointed Concrete Pavement

(16.1 square yards to 48.0

square yards) (10" Thick)

467.96 Yd3

526.39 2037

1153.39

Table 175 (cont.)

272

Proposal number

and district

Letting date

Item description

Price

at letting date

per unit

Unit

Net present

value ($)

(2017)

Year of

occurrence

Cost at year

of occurrence

($)

H.009574.6

(Shreveport)

5/14/2014

Full Depth Patching of

Jointed Concrete Pavement

(16.1 square yards to 48.0

square yards) (10" Thick)

467.96 Yd3

526.39 2047

1707.30

H.003200.6

(Lake Charles)

5/13/2015

Saw Cutting Portland

Cement Concrete Pavement

2.63

INLF

2.84 2037 6.23

H.003200.6

(Lake Charles)

5/13/2015

Saw Cutting Portland

Cement Concrete Pavement

2.63

INLF

2.84 2047 9.22

Net present value at 2017 for selected items 189329.02

273

In assigning an economic score for this study case, there is an economic score of 0.5; the final

economic score after assigning the economic score can be calculated using Equation 17.

Economic score for alternative 5 = 0.266×0.5 = 0.133. The best alternative is alternative 5

(lowest score) in both cases (material only or overall bid item material)

Table 176. Cost analysis for alternatives (scenario 1)

Alternative Initial cost

(material)

Maintenance and

rehabilitation

item

Total

($/design) Weighted

Assigning

economic

score

5 255980.60 4950.465 260931.07 0.266 0.133

6 255980.60 7858.60 263839.20 0.269 0.134

7 264584.99 189329.02 453914.01 0.463 0.231

Table 177. Cost analysis for alternatives (scenario 2)

Alternative Initial cost

(overall)

Maintenance and

rehabilitation

item

Total

($/design) Weighted

Assigning

economic

score

5 527615.23 4950.465 532565.70 0.274 0.137

6 677513.81 7858.60 685372.41 0.352 0.176

7 536058.60 189329.02 725387.62 0.373 0.186

5.3.3.10 Total sustainability score

The total score can then be calculated using Equation 18:

overall final sustainability score = weighted economic score for alternative + weighted

environmental impact for alternative. All the resulting values are illustrated in Table 178.

Alternative 5 has the lowest total sustainability score in both scenarios.

Table 178. Total score

Alternative Economic score Environmental

score

Total score

Scenario 1 Scenario 2 Scenario 1 Scenario 2

5 0.133 0.137 0.169 0.302 0.306

6 0.134 0.176 0.166 0.30 0.342

7 0.231 0.186 0.165 0.396 0.351

5.3.3.11 Statistical analysis

To be able to compare statistical significance of the results, another EPD will be used

to assess the environmental impact. Note that the economic impact cannot be compared

274

because cost data does not exist for states other than Louisiana. A compressive strength value

of 4400, 5000 and 6000 psi will be used to evaluate the following environmental

impact/inventory values: GWP, ODP, AP, EP, POCP, RE and NRE.

The scope will include the following stages: raw material extraction, transportation

from raw material extraction to manufacturing, manufacturing, and transportation from

manufacturing to project location. The total environmental score will be compared, since the

breakdown for EPD is not available for states other than Louisiana. The same procedure will

be followed to evaluate the total environmental impact with the same assumptions, only raw

data from EPD will change. The raw data used, extracted from EPD, for compressive strength

value of 4400 psi are illustrated in Table 179, as a sample. These are the same samples

selected for Hammond parish

Table 179. Total environmental impact per alternative

Alternative GWP

kg CO2

eq/ yd3

ODP

kg CFC-11 eq/

yd3

AP

kg SO2 eq/

yd3

EP

kg N eq/

yd3

POCP

kg O3 eq/

yd3

NRE

MJ/

yd3

RE

MJ/

yd3

5A 305.83 3.51E-06 1.69 0.05 24.31 1673.67 12.54

6B 262.25 3.07E-06 1.48 0.04 21.48 1488.64 10.77

7C 255.37 2.97E-06 1.44 0.04 21.25 1433.59 10.57

Average 274.48 3.18E-06 1.54 0.04 22.35 1531.97 11.29

Final results for the environmental score are illustrated in Table 180. To better

understand the data used, descriptive statistics is illustrated in Table 181, including the mean,

the standard deviation, and confidence interval. To evaluate results significance, analysis of

variance (ANOVA) is performed with a confidence interval of 95%. The resulting P value =1

( > 0.001 indicating insignificance of the results).

275

Table 180. Environmental impact comparison

Alternative Environmental

score

(Louisiana)

Environmental

score

(4400 psi)

Environmental

score

(5000 psi)

Environmental

score

(6000 psi)

5 0.169 0.1696 0.1675 0.1659

6 0.166 0.1656 0.1683 0.1668

7 0.165 0.1648 0.1642 0.1674

Mean 0.166667 0.166667 0.166667 0.1667

Standard

deviation 0.002082 0.002572 0.002173 0.000755

Table 181. Descriptive statistics for the environmental impact values

Criteria

Louisiana

data

4400

psi

5000

psi

6000

psi

Mean 0.166667 0.166667 0.166667 0.1667

Standard error 0.001202 0.001485 0.001255 0.000436

Median 0.166 0.1656 0.1675 0.1668

Standard deviation 0.002082 0.002572 0.002173 0.000755

Sample variance 4.33E-06 6.61E-06 4.72E-06 5.7E-07

Skewness 1.293343 1.545393 -1.47178 -0.58558

Range 0.004 0.0048 0.0041 0.0015

Minimum 0.165 0.1648 0.1642 0.1659

Maximum 0.169 0.1696 0.1683 0.1674

Sum 0.5 0.5 0.5 0.5001

Count 3 3 3 3

Confidence level

(95.0%) 0.005171 0.006388 0.005399 0.001875

Table 182. Analysis of variance results

Source of

Variation SS df MS F P-value F critical

Between

Groups 2.5E-09 3 8.33E-10 0.000205 1 4.066181

Within

Groups 3.25E-05 8 4.06E-06

Total 3.25E-05 11

5.3.3.12 Sensitivity analysis

Sensitivity analysis is an important criteria in decision making. Sensitivity analysis should

determine the sensitivity of an output to a change in input, while keeping all the other

alternatives constant. In this section, sensitivity analysis will be performed to evaluate how

276

the change in the following criteria affects the total environmental impact for each

alternative.

1) Environmental impact of raw material extraction and manufacturing (reported from EPD)

2) Environmental impact of transportation

a) From raw material extraction to manufacturing (from EPD)

b) From manufacturing to project location

c) Total environmental impact of transportation from raw material extraction to

manufacturing and from manufacturing to project location

3) Impact of total distance traveled from raw material extraction to project location.

The sensitivity levels that will be evaluated by an increase of 10% in the previous factors.

Final results are illustrated in Table 183

Table 183. Sensitivity analysis and final environmental impact

Criteria Change on total

environmental impact (%)

Environmental impact of raw

material extraction and

manufacturing (reported from

EPD)

0.341

Environmental impact of

transportation (from raw material

extraction to manufacturing)

0.071

Environmental impact of

transportation

(from manufacturing to project

location), by changing the

inventory values/environmental

impact of heavy duty truck

9.587

Total distance traveled from

manufacturing to project location

9.587

Environmental impact of total

transportation module

(transportation from raw material

extraction to manufacturing and

from manufacturing to project

location)

9.658

277

By further interpretation for the results illustrated in Table 183, it is clear that the final

environmental impacts are highly altered by changing criteria in the transportation module:

either in changing the environmental impact of the transportation stage from manufacturing

to project location, by changing the total distance traveled from manufacturing to project

location, or by changing the total environmental impact of transportation (transportation from

raw material extraction to manufacturing and from manufacturing to project location).

As for changing raw material extraction and manufacturing stages of concrete,

changing these criteria did not change the total environmental impact compared to the

transportation stages. This example illustrates the importance of the transportation module

and proves that it represents a sensitive criteria towards the total environmental impact.

5.3.4 CASE STUDY 4: BENCHMARKING MODULE

The same case study will be performed using the benchmarking module for

illustration. A step by step procedure will be displayed. The same procedure and format will

be followed in this module.

5.3.4.1 Environmental impact

1. Select the state you want to use the mix design: The state is Louisiana.

2. The purpose of the design is benchmarking. The stakeholder is interested in

benchmarking the product, and wants to know whether the product is below or above the

average.

3. Select the number of products to benchmark: The stakeholder might choose to benchmark

the product with respect to various criteria, including a certain region for example, either

with respect to the Shreveport district or with respect to a specific parish. Also, the user

might want to measure the cost of the product to know whether the product is above or

below the market average.

278

4. Assign weights for the environmental and economic impacts. Both impacts will be

assigned a weight of 0.5.

5. Convert the modulus of rupture to compressive strength value, using Equation 8, where:

MOR (psi) = 2.3 (fc)2/3 or fc= (MOR/2.3)3/2.

This results in a compressive strength value of (600/2.3)3/2 = 4213 psi

6. Select alternative mixes from the EPD data, to evaluate the environmental impact. The

user enters a specific mix design (required by the design) to look for its environmental

impact in the database. The stakeholder is interested in getting cement content around the

500 lb value. The mixes are illustrated in Table 184. The same procedure used in

alternative design comparison will be applied here.

Table 184. Required mix design

Cement

(lb)

Fly

ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Air

entertainer

(%)

500 100 1501 1520 750 29 3

This exact mix design is not in the database; therefore, the stakeholder can select from

among the existing mixes. The nearest mixes, based on the cement amount, are illustrated in

Table 185. In Table 185, there are various mix designs that appear. There should be some

filtering criteria for the stakeholder. For example, one of the filtering criteria can show the

proximity to project location. The user will select the benchmark for the product with respect

to all the mixes produced in the Shreveport district.

This narrows down the mixes to options 5, 6, and 7 (based on user selection). The

new selections are illustrated in Table 186. Now the design will proceed with the average

results and not with the individual mix designs. The average value was calculated, using

Equation 19.

Benchmarking = ∑ environmental impact/ total number of mixes

279

In case the user wants to benchmark his product with respect to the Shreveport

district, the average cement content in the mix designs is around 508 lb, and the fly ash is

around 0 lb. The average price for the mixes in this area is $120.33. All values are illustrated

in Table 186.

The environmental impact of the mixes 5, 6, and 7 are illustrated in Table 187. These

are the values extracted from EPD, with no modifications. Values showing the environmental

impact values will be averaged, and the design will proceed with the average value. This is

one of the differences between the alternative design module and the benchmarking module.

As illustrated, the values are given per 1 yd3. These are the impacts for A1: raw material

extraction and A3: manufacturing.

These values are given per 1 yd3; some adjustments must be performed to adjust the

environmental impacts per the total design volume.

The total design volume calculation is illustrated in Table 188 for the 11 inch thickness. The

calculation was performed using Equation 6: Lv = LT×LW× LL. This step remains the same,

since the design will not change.

The total environmental impact for the design then should be adjusted according to

the overall design volume, using Equation 7.

For example, the total adjusted GWP for the average value is:

Which means the volume 2151.09 yd3 × 236.34 kg CO2 eq/yd3= 508384.304 kg CO2 eq

The environmental impact will be adjusted accordingly for each alternative. Final results are

indicated in Table 189.

As illustrated, the values have different units. Therefore, these should be normalized

to have consistent, unitless units that can be summed up altogether in the end.

280

Table 185. Corresponding mix design

Alternative Cement

(lb)

Fly ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Water

reducer

(oz)

District

Initial

cost

($/yd3)

1 517 0 1235.00 1332.00 450 30.9 23.23 Hammond 112

2 510 0 1052.00 1638.00 402 28.1 30.8 Lafayette 116

3 517 0 1006.00 1488.00 555 29.4 2.5 Lafayette 116

4 545 0 1445.00 390 1446.00 28.8 21.8 New Orleans 155

5 508 0 737 1698.00 752 29.5 30.5 Shreveport 119

6 508 0 1737.00 1698.00 752 29.2 20.3 Shreveport 119

7 508 0 730 1698.00 752 29.2 20.3 Shreveport 123

Table 186. Filtering criteria based on manufacturer location

Alternative

Cement

(lb)

Fly

ash

(lb)

Fine

aggregate

(lb)

Coarse

aggregate 1

(lb)

Coarse

aggregate 2

(lb)

Mixing

water

(gallons)

Water

reducer

(oz)

District

Initial

cost

($/yd3)

5 508 0 737.00 1698.00 752 29.5 30.5 Shreveport 119

6 508 0 1737.00 1698.00 752 29.2 20.3 Shreveport 119

7 508 0 730.00 1698.00 752 29.2 20.3 Shreveport 123

Average 508 0 1698.00 1698.00 752 29.300 23.700 Shreveport 120.33

281

Table 187. Environmental impact extracted from EPD (Al and A3)

Alternative

GWP

kg CO2

eq/yd3

ODP

kg CFC-11

eq/yd3

AP

kg SO2

eq/yd3

EP

kg N

eq/yd3

POCP

kg O3

eq/yd3

NRE

MJ/yd3

RE

MJ/yd3

5 235.88 3.23E-06 0.96 0.10 15.94 1681.57 190.54

6 237.33 3.34E-06 0.97 0.10 16.18 1705.44 192.74

7 235.79 3.23E-06 0.96 0.10 15.93 1679.69 190.53

Average 236.34 3.27E-06 0.97 0.11 16.02 1688.90 191.28

Table 188. Final layer volume

Dimension Value Unit Unit conversion Final unit

Layer Thickness 11 Inch 1/36 Yd

Length 1 Mile 1760 Yd

Width 12 Feet 0.33 Yd

Total volume 2151.09 Yd3

Table 189. Adjusted environmental impact per volume

Alternative

GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

Average 508384.30 0.007 2089.60 229.09 34464.49 3632999.10 411453.30

The normalization values used are illustrated in Table 190. This step is the same as

previously noted.

Table 190. Normalization values used

GWP (kg CO2 eq/ yd3) 24000

ODP (kg CFC-11 eq/yd3) 0.160

AP (kg SO2 eq/yd3) 91

EP (kg N eq/yd3) 22

POCP (kg O3 eq/yd3) 1400

NRE (MJ/yd3) 288572.509

RE (MJ/yd3) 24874.54785

The normalization can be performed by dividing the environmental impact per the

normalization value. This can be accomplished by following Equation 2.

For example, the normalization value for the GWP for the average value is:

282

508384.304kg CO2 eq/24000 kg CO2 eq = 21.183. Final normalization values are indicated in

Table 191.

Table 191. Normalized value for adjusted environmental impact per total volume

Alternative GWP ODP AP EP POCP NRE RE

Average 21.183 0.044 22.963 10.414 24.617 12.590 16.541

5.3.4.2 Transportation impact

Transportation from the raw material extraction to the manufacturing phase. These are given

per Athena Institute for each mix design. The values are given per 1 yd3. The values are

illustrated in Table 192. These values should be adjusted to total design volume. Since this is

the benchmarking module, the average value is computed to work as necessary.

Table 192. Transportation from raw material extraction to manufacturing (A2)

Alternative

GWP

kg CO2

eq/ yd3

ODP

kg CFC-11

eq/yd3

AP

kg SO2

eq/yd3

EP

kg N

eq/yd3

POCP

kg O3

eq/yd3

NRE

MJ/

yd3

RE

MJ/

yd3

5 23.040 8.76E-10 0.163 0.0091 4.64 315.90 0.00

6 28.948 1.10E-09 0.200 0.0111 5.69 396.93 0.00

7 22.981 8.74E-10 0.162 0.0090 4.63 315.10 0.00

Average 24.99 9.50E-10 0.18 0.01 4.99 342.65 0.00

The adjustment process is illustrated in Table 193, which is performed by multiplying

the values in Table 192 by the total design volume. For example, the adjusted GWP for the

average alternative = 24.99 kg CO2 eq/ yd3×2151.09 yd3 = 53756.655kg CO2 eq. The final

values are illustrated in Table 193.

Table 193. Adjusted transportation impact per design volume

GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

53756.65 0.00 377.27 21.08 9985.03 737069.46 0.00

Part 2 Transportation impact from the raw material extraction to project location

To calculate the transportation impact from the raw material extraction to project location, the

distance between the manufacturers to project location should be determined. This can be

accomplished through calculating the distance between the two zip codes: the zip code of the

283

project location, as well as the manufacturer zip code. The zip code of the project location is

71107, and the manufacturer zip codes are user input, as indicated in Table 194. The distance

can be calculated using Google maps. Results in Table 194 indicate that the transportation

values are similar, since the manufacturer is in the Shreveport area for all alternatives. The

average transportation distance is 31.66 miles or 21.86 kms. The average distance will be

used.

Table 194. Total transportation distance (manufacturer to project location)

Alternative

number

Project

location

Manufacturer

location

Total distance

(miles)

Total distance

(km)

5 71107 71108 13 20.80

6 71107 71111 14 22.40

7 71107 71111 14 22.40

Average 13.66 21.86

Also, the total weight to be transported should be identified. The transportation will

be performed using a heavy duty truck with a weight of 80,000 lb and diesel fuel. The

average weight of concrete to be transported is illustrated in Table 195. These values exist in

the database (originally gathered from the manufacturer). As previously described, the total

weight to be transported is the vehicle weight and the total weight of concrete to be

transported.

This can be accomplished through using Equation 9: M = D ×Lv

For example, the density for the average alternative = 3877.89 lb/yd3 and the total

design volume = 2151.09 yd3; therefore, the total average design weight = 3877.89

lb/yd3×2151.09 yd3 = 8341712.04 lb. Then this weight value should be converted to metric

ton, which will be accomplished by multiplying the value by a factor of 0.00045359

The average concrete weight to be transported = 8341712.04 lb × 0.00045359 = 3783.72 ton.

The total weight to be transported for the average alternative is therefore the sum of

the truck weight, as well as the average concrete transported. To obtain the total number of

loads required to transport the total concrete, Equation 10 should be used

284

=8341712.04 lb/54000 lb = 154.5 loads

Table 195. Weight of concrete to transport

Alternative

number

Density

(lb/yd3)

Total

weight per

design

volume of

concrete

(lb)

Weight

of

concrete

(ton)

Truck

weight

(ton)

Total

number

of loads

Total

weight

(truck+

concrete)

(ton)

Average 3877.89 8341712.04 3783.72 36.28 154.5 3820

To adjust the inventory values coming from the transportation module, Equation 11

should be used:

×total number of trucks

The emissions/ inventory for the heavy duty truck is illustrated in Table 196.

Table 196. Heavy duty truck emissions

Global

Warming Air

kg CO2 eq

Ozone

Depletion

Air kg CFC-

11 eq

Acidification

Air

kg SO2 eq

Eutrophicat

ion

Water

kg N eq

Smog

Air

kg O3 eq

Fossil Fuel

depletion

MJ

3.24E-01 0.00E+00 1.34E-03 5.55E-04 4.62E-02 8.09E-02

For example, to calculate the transportation impact from the manufacturing to the

project location for GWP, Adjusted inventory values = 2 × 0.324 kg CO2/ton.km × 3820 ton

×21.86 km ×154.5 =8361475.1 kg CO2 eq. Values are illustrated in Table 197.

Total transportation impact. The total transportation impact is the sum of Part 1

(transportation from raw material extraction to manufacturing) and Part 2 (transportation

from the manufacturer to project location). Values are illustrated in Table 198. These values

should be added and then normalized.

To normalize the total transportation impact values, each environmental impact

should be divided by the corresponding normalization value. For example, the average mix

285

design will have the following value after normalization (for GWP) = 8415231.83 kg CO2 eq/

24000 kg CO2 eq =350.63 .The total transportation values are illustrated in Table 199 for the

three alternatives.

5.3.4.3 Total environmental impact

The total environmental impact is the total of the environmental impact coming from

concrete design (EPD), as well as the total transportation impact (from raw material

extraction to manufacturing and from manufacturing to project location). This will result

from the values given in Table 200. For example, the environmental impact extracted from

EPD and adjusted based on design volume was previously described:

Environmental impact from EPD (adjusted per volume) + total transportation impact

= 508384.30kg CO2 eq + 8415231.83CO2 eq =8923616.13kg CO2. These total environmental

impacts must be normalized. Values after normalization are illustrated in Table 201.

5.3.4.4 Weighing the environmental impact

Based on stakeholder preference, weighting can be assigned to the average environmental

impacts. The weighting procedure will be used here for demonstration. The weights used are

illustrated in Table 197.

Table 197. Transportation impact from the manufacturer to project location

Alternative GWP

kg CO2

eq

ODP

kg CFC-

11 eq

AP

kg SO2-

eq

EP

kg N eq

POCP

kg O3 eq

NRE

MJ

RE

MJ

Average 8361475.17 0.00 34581.40 14322.89 1192284.42 2087788.09 0.00

Table 198. Total transportation impact per alternative

Alternative GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

Average 8415231.83 0.00 34958.68 14343.97 1202269.46 2824857.55 0.00

Table 199. Total normalized transportation impact per alternative

Alternative GWP ODP AP EP POCP NRE RE

Average 350.63 0.00 384.16 651.99 858.76 9.78 0.00

286

Table 200. Total environmental impact per alternative

Alternative GWP

kg CO2

eq

ODP

kg CFC-11

eq

AP

kg SO2

eq

EP

kg N

eq

POCP

kg O3

eq

NRE

MJ

RE

MJ

Average 8923616.13 0.007 37048.28 14573.07 1236733.95 6457856.66 411453.30

Table 201. Normalization values for the total environmental impacts

Alternative GWP ODP AP EP POCP NRE RE

Average 371.817 0.044 407.124 662.413 883.381 22.379 16.541

Table 202. Weights used in the study

GWP ODP AP EP POCP NRE RE Total

0.200 0.150 0.150 0.150 0.150 0.100 0.100 1

The sum of all the environmental values together is the total environmental score for

the average impact, minus the RE value. GWP+ODP+AP+POCP+NRE-RE = 367.8

Here the relative score does not exist, since the average value is taken. Values are

illustrated in Table 203. In the event the stakeholder assigned a weight for the environmental

score (since the assigned weight is 0.5), then the final environmental score after adjusting per

the weight may be calculated using Equation 15. The weighted environmental score per

alternative =

For example, for the average alternative, the weighted score = 0.5 × 367.892= 183.946

Calculations are illustrated in Table 203.

Table 203. Total environmental impact after normalizing and weighting

Alternative GWP ODP AP EP POCP NRE RE Total

Average 74.363 0.007 61.069 99.362 132.507 2.238 1.654 367.89

5.3.4.5 Economic impact

As previously described, the economic analysis will be accomplished by performing a

complete lifecycle cost analysis for each alternative. This was calculated earlier in the

alternative design module. However, while values will not be treated individually, the

average will be taken for the benchmarking module. As illustrated in Tables 204 and 205, the

287

average material cost adjusted to total design volume is $258,848.73, and the total initial cost

(as a bid item) is $58,0395.88. The average cost for each maintenance and rehabilitation

activities is illustrated per activity in Table 204, 205, and 206. The stakeholder can

benchmark with respect to these values.

Table 204. Cost analysis for alternatives (scenario 1)

Alternative Initial cost

(material)

5 255980.60

6 255980.60

7 264584.99

Average 258848.73

Table 205. Cost analysis for alternatives (scenario 2)

Alternative Initial cost

(overall)

5 527615.23

6 677513.81

7 536058.60

Average 580395.88

Table 206. Average maintenance and rehabilitation activities

Item Design 5 ($) Design 6 ($) Design 7 ($) Average ($)

Full Depth Patching of

Jointed Concrete Pavement

(16.1 square yards to 48.0

square yards) (10" Thick)

425.16 502.25 526.39 484.6/ Yd3

Cleaning and Sealing

Random Cracks

4097.97

6852.79 188270.54

66407.1/ Mile

Saw Cutting Portland

Cement Concrete

Pavement

1.08 0.64 2.84 1.52/ INLF

5.4 SUMMARY

• This chapter presented various case studies in various states/climatic regions to test the

newly developed framework. The software was used for both alternative designs

comparison and benchmarking.

• For alternative designs comparison, the data associated with each state was used (For

example, for Texas, the EPD data associated with the State of Texas was used and the

288

Pavement ME software was calibrated for the State of Texas, with the same approach

followed same for the State of Louisiana, etc…).

• For benchmarking; the user can select any region and benchmark his product with respect

to it. He can also filter the database with respect to many criteria. such as the compressive

strength value and the mix design breakdown.

5.5 REFERENCES

Breakah, TM, et al. "Effects of Using Accurate Climatic Conditions for Mechanistic-

Empirical Pavement Design." Journal of Transportation Engineering-Asce, vol. 137,

no. 1, n.d., pp. 84-90. EBSCOhost,

libezp.lib.lsu.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=e

dswsc&AN=000285476100010&site=eds-live&scope=site&profile=eds-main.

Furuholt, E. (1995). Lifecycle assessment of gasoline and diesel. Retrieved January 21, 2017,

from http://www.sciencedirect.com/science/article/pii/092134499500020J

Mack, J., Josef, F., Gregory, J., Kirchain,, R., Akbarian, M., Swei, O., & Wildnauer, M.

(2012). Designing Sustainable Concrete Pavements using the Pavement-ME

Mechanistic Empirical Pavement Design and Life Cycle Analysis. Retrieved 2016,

from https://cshub.mit.edu/sites/default/files/documents/mack-Sustainable-PCC-

Pavements-2012.pdf

Rao, c., & Darter, m. (2003). Evaluation of internally cured concrete for paving applications.

Retrieved august 1, 2016, from

http://www.escsi.org/uploadedfiles/technical_docs/internal_curing/eval of ICC for

paving apps report.pdf

Resource Conservation Program. (2017). Retrieved from

http://www.dot.ca.gov/hq/oppd/rescons/sustainable.htm

Samuels, D. (2013). Central Thruway, new road connecting Central to I-12, opens Thursday.

Retrieved April 17, 2017, from http://www.nola.com/traffic/baton-

rouge/index.ssf/2013/07/central_thruway_new_road_conne.html

Sustainability Implementation Action Plan. (2016). Retrieved from

http://www.dot.ca.gov/sustainability/docs/2016_Sustainability_Implementation_Actio

n_Plan_First_Ed_092016.pdf

Temple, W., Zhang, Z., & Lambert, J. (2004). Agency Process for Alternate Design and

Alternate Bid of Pavements . Transportation Research Board Annual Meeting.

Retrieved December, 2016, from http://www.ltrc.lsu.edu/pdf/TRB2004-001293.pdf

289

Thomas R. Karl and Walter James Koss. (1984): "Regional and National Monthly, Seasonal,

and Annual Temperature Weighted by Area, 1895-1983." Historical Climatology

Series 4-3, National Climatic Data Center, Asheville, NC, 38 pp. Retrieved from

http://www.worldcat.org/title/regional-and-national-monthly-seasonal-and-annual-

temperature-weighted-by-area-1895-1983/oclc/12798609

Tia, M., Verdugo, D., & Kwon, O. (2012). Evaluation of long life concrete pavement

practices for use in Florida. Retrieved from

https://ntl.bts.gov/lib/46000/46600/46654/FDOT-BDK75-977-48-rpt.pdf

Wilde, W., Waalkes, S., & Harrison, R. (1999). Lifecycle cost analysis of Portland cement

concrete pavements. Retrieved April 15, 2016, from

http://www.utexas.edu/research/ctr/pdf_reports/1739_1.pdf

Wu, Z., & Xiao, D. (2016). Development of DARWin-ME Design Guideline for Louisiana

Pavement Design . Retrieved December, 2016, from

http://www.ltrc.lsu.edu/pdf/2016/FR_551.pdf

290

CHAPTER 6. FINDINGS, CONCLUSION, DISCUSSION, AND FUTURE WORK

The objective for this study was to develop a decision making tool to evaluate rigid

pavement design sustainability (applying two pillars of environmental and economic criteria)

for the State of Louisiana. The scope is inclusive of cradle to gate, as well as the

transportation stage from the manufacturer to project location.

To achieve this objective, the first question was how to integrate the sustainability

criteria, since the existing framework contains no sustainability criteria. This involved a

change to the original rigid pavement design framework in order to enable the inclusion of a

new factor.

To evaluate the environmental aspect of sustainability, an extensive literature review

was performed. The most widely used tool to evaluate the environmental impact of a product

is LCA. However, LCA has various drawbacks. When applied by various researchers in an

inconsistent way, a lack of comparability arises, due to reasons such as the use of a different

system boundary, different geographic locations, or different data sources. These unforeseen

inconsistencies can lead to an incomparability across studies.

To solve this issue, this study used data from EPD. EPD is defined as quantified

environmental data for a product, based on a pre-set category of parameters, which in turn

were established to homogenize assumptions while performing an LCA. In fact, EPDs follow

the same LCA procedure for quantifying the environmental impact. However, the method

used to issue an EPD guarantees consistency in the data collection process, thus enabling a

comparison between products fulfilling the same function.

To evaluate the economic impact, cost data was collected for the State of Louisiana in

order to perform a full lifecycle cost analysis. This involved collecting costs occurring at the

present (mostly material costs), as well as maintenance and rehabilitation cost items

occurring in the future. The initial cost was collected from manufacturers, and the

291

maintenance and rehabilitation items were collected from LaDOTD. To evaluate the

Transportation impact from the manufacturer to project location, a Lifecycle inventory for

various types of trucks and fuel was used, and an LCA was performed to evaluate the

environmental impact. Additionally, to facilitate the use and querying of all data, these data

were stored in a database format. A new software/tool was developed with a simple user

interface to facilitate data manipulation.

The developed software follows the methodology of the framework, as previously

illustrated. The software can accommodate work on two modules; the first module is the

product comparison module, while the second module is the benchmarking module. The

product comparison module enables the comparison of various products based on economic

and environmental scores. The stakeholder can then select the product based on a weighted

average between the environmental and economic criteria. Moreover, the benchmarking

module enables the user to benchmark the product with respect to various criteria, such as

mix design breakdown, compressive strength value, or a certain geographic location.

The developed framework/tool also has other applications, which form a bigger

picture, such as accounting, decision making, and process improvement. The accounting

method is the process of measurement for the sake of reporting. This is mostly used to

respond to laws and mandates requiring quantifications of emissions, such as the cap and

trade legislation. Both modules (product comparison and benchmarking) can aid the

accounting method. For example, the product comparison module may help to quantify the

total emissions released during concrete production which at times are required by law, such

as the California mandate.

Moreover, the benchmarking module can help the user to measure the impact of the

product with respect to the market average. By benchmarking, the user can then lower the

292

emissions, in case such emissions exceed the average limit. Also, the benchmarking module

will allow the stakeholder to benchmark the product for certification for the LEED credit.

Also, the developed framework works for process improvement. The benchmarking

module allows the stakeholder to benchmark the product with respect to similar products

(such as similar compressive strength value, mix design breakdown, or geographic location),

in order to find whether the environmental impact of the product is below or above the

average. In the event the product is above average, more process improvement should be

performed to achieve a lower environmental impact. An improvement might involve the use

of more advanced technology, or more research and development

The study performed various case studies in different locations to validate the

framework. Case studies included the State of Texas and the State of Louisiana. The

framework was used in both the benchmarking module and the product comparison module.

For the product comparison module, the framework was used to evaluate the sustainability

score for various mix designs based on a single sustainability score. By examining the total

score, one could estimate which product has higher or lower environmental and/or economic

impact. However, by evaluating results significance at a confidence interval of 95%, the final

sustainability scores proved to be insignificant. This was based on a sample size of three.

However, these values might change by changing the sample size or the database used. For

this reason, descriptive statistics were also provided including a confidence interval, to allow

the user to make a decision.

Also, to answer the research questions of this study, the framework was used to test

how sensitive the total environmental impact of a product (from cradle to gate and the

transportation stage from manufacturing to project location) would be, in regard to the

transportation stage vs. changing the environmental impact coming from raw material

extraction and manufacturing stages. This was performed by performing a sensitivity analysis

293

for the following criteria and observing the final results for the a) environmental impact of

raw material extraction and manufacturing (reported from EPD), b) the environmental impact

of transportation (from raw material extraction to manufacturing), c) the environmental

impact of transportation (from manufacturing to project location), d) by changing the

inventory values/environmental impact of heavy duty truck, e) the total distance traveled

from manufacturing to project location, and f) the environmental impact of total

transportation module (transportation from raw material extraction to manufacturing and

from manufacturing to project location).

Results proved that the total environmental impact is more sensitive to changing the

following criteria: environmental impact of transportation(from manufacturing to project

location), by changing the inventory values/environmental impact of heavy duty truck, total

distance traveled from manufacturing to project location, and environmental impact of total

transportation module (transportation from raw material extraction to manufacturing and

from manufacturing to project location), more than changing values of raw material

extraction and manufacturing stages. For example, by varying each of the previous values by

10%, the final environmental impacts increased by around 0.10% when varying the

environmental impacts from raw material extraction and manufacturing stages. However, the

final environmental impact changes by approximately 0.0259% when varying the

environmental impact of transportation from raw material extraction to manufacturing. When

varying the remaining criteria, the final environmental impact increased by 9.86%. This

finding also explains, the insignificance of the final results, when changing the EPD used.

This is due to the fact that the transportation module from the manufacturing to project

location, the total distance traveled, proved to contribute more to final environmental

impacts, more than raw material extraction, manufacturing, and the transportation stage from

raw material extraction to manufacturing.

294

6.1 DISCUSSION

Case studies included various states in order to validate the framework in different

climatic regions in the South. The designs performed included internally cured concrete in

Texas, as well as the evaluation of existing pavement design sustainability in Louisiana.

Results and analysis of case studies established the following: The case study for Texas

showed that internally cured concrete proved to be a better option than conventional concrete

on the economic level, as well as on the environmental level. This outcome emanates from

the fact that the use of internally cured concrete enables the use of smaller design thicknesses,

thus leading to lower environmental impacts, as well as economic impacts. This reinforces

the finding that this framework can be validated anywhere, as far as data are available (both

environmental and economic). Notably, the economic data for the case study performed in

Texas does not exist in the study database/software, and thus the data were collected from the

project.

The case study for Louisiana: The situation in Louisiana was different from other states,

which had previously issued EPDs. A survey was performed in Louisiana to assess

companies that issued individual EPDs earlier, or participated in industry wide averaging of

EPDs. The results revealed that there are five companies and a total of sixteen plants that

have already participated in an industry wide average EPD study with the National Ready

Mix Concrete Association. Contact with the consultant (Athena Institute) revealed that there

exists no environmental impact/inventory matrix solely for the State of Louisiana. Data for

the southern region (including states other than Louisiana) were compiled to produce an

environmental impact and inventory matrix for the southern region.

To produce an EPD for Louisiana based on the survey performed, the aggregated data of the

five companies and the sixteen plants were averaged to produce an environmental

impact/inventory matrix for the State of Louisiana.

295

Case studies performed in Louisiana were very specific for each mix design. Each

mix design was tracked for both environmental and economic impacts. Therefore, when

performing an analysis between various products, results will be as accurate as the available

data.

Results of the sensitivity analysis performed highlight the importance of the

transportation stage in a product lifecycle, contributing to higher environmental impacts vs.

raw material extraction and manufacturing. This finding should push stakeholders to limit the

total distance traveled by a truck. This can be accomplished by ordering concrete from the

nearest available manufacturer, if possible. Also, this finding might encourage stakeholders to

find more sustainable technologies to reduce emissions resulting from transportation.

By examining concrete and cement production processes, it is revealed that cement

has an intensive production process requiring energy. Despite this, there remain problems

associated with the data/inventory values that are available for the energy used during the

production process. Also, data associated with the clinker are not accurately used, in an event

where the clinker is imported and yet treated as a local material. This lack of data has various

drawbacks. First, researchers do not have data to accurately model local data. Second,

companies might not be able to benchmark their products with respect to available data. This

might prevent the process improvement, or hinder the use of a better technology, since there

is no accurate data for companies to benchmark their performance with respect to the local

market.

Moreover, as concrete is a mixture of various products, the process of allocation

should be well understood. However, this is not the current case. The lack of knowledge

regarding the allocation process also leads to inaccurate results, which would mislead

researchers and decision makers about the actual environmental impact of issues associated

with concrete.

296

Another point to highlight is the importance of inclusion of all the environmental

impacts that result during the production of concrete. This is really critical, should the

concrete contain chemical items. However, this concern is not currently taken into

consideration, which will have environmental as well as health impacts.

6.2 STUDY LIMITATIONS

The limitation of this study is mostly associated with the data limitation. First, there were

many problems associated with the data collection process for both EPD and cost analysis

data. For the EPD data collection process, many issues associated with the data proprietary

issues, especially for the State of Louisiana, culminated with issuing an industry wide

average EPD, rather than individual EPDs for companies. Companies were reluctant to give

relevant information, due to concerns regarding any loss of competitiveness in the market. As

for the scope, the environmental impact was limited to cradle to gate analysis only, which

should be expanded in the future.

Concerning the economic aspect and cost data for Louisiana, many issues were

involved in this data collection process as well. In order to compile the history for pavement

maintenance and rehabilitation items, the history necessary for data was tracked back for 20

to 30 years, which provided not only relatively old data, but the absence of some information,

which could not be located. In addition, the older cost data was no longer available. To solve

this problem, the compressive strength values of the selected mix designs were matched to

the compressive strength values for old mix designs/projects. As a result, the maintenance

and rehabilitation items were matched accordingly.

The study only included two pillars of sustainability, the economic and the

environmental aspects, and did not include the social pillar of sustainability. This is due to the

fact that the social lifecycle assessment models are not yet fully developed. The scope of the

study was only limited to cradle to gate analysis (since this is the scope of EPD) and did not

297

cover all pavement lifecycle phases from cradle to grave. Also, the study did not include an

economic analysis (or lifecycle cost analysis) for states other than Louisiana, which makes it

difficult to perform a lifecycle cost analysis for states other than Louisiana.

6.3 FUTURE WORK

• This study presented existing problems in pavement LCA per lifecycle phase. General

shortcomings about performing LCA in general include: the use of different system

boundaries, the use of different functional units, and the use of different data sources;

these obstacles made the overall comparison between studies almost impossible.

• More work should be performed in the material extraction phase, such as issues related to

feedstock energy. For the use phase, more research should be performed that relate all

factors involved in the use phase together, such as noise, lighting, leachate, etc.; the

impact of all these items interacting has not yet been studied.

• The construction phase should be considered in performance of more work-related

activities, such as equipment mobilization and demobilization, equipment use at the site,

and transport of materials from the site to the final disposal option, as well as traffic

congestion related to construction activities.

• The maintenance and rehabilitation phase should be project-specific for future study; the

timings of the activities should be calculated for each project, since such data cannot be

generalized for all projects.

• For the end of life option, not only should more work be performed in allocation methods,

but also more research should be extended to determine the exact amount of concrete

going to recycling/or landfill.

• As for the lifecycle assessment of concrete vs. cement, there remain various unexplored

areas, such as raw material preparation, grinding, milling, and transportation stages for

Portland cement. As for Portland cement concrete, more work should be performed with a

298

focus on studying the inclusion of admixtures and allocation criteria. Also, since not all of

the environmental impacts were studied, future research should examine environmental

impacts, such as Volatile Organic Compounds.

• Also, accurate information should be used when using imported clinker, mostly to

identify the country of origin and the data source, rather than local data.

• For future work, this study recommends an expansion of software to evaluate the

sustainability of other materials (such as aggregates and steel), whenever the EPDs

become available.

• As for future work related to the developed framework and its scope; future work might

also focus on expanding the scope of the work to evaluate the environmental impact from

cradle to grave, rather than from cradle to gate, as in this study.

• Also, future studies might include cost data for other states, since EPDs were collected for

other states as well. In this manner, a full lifecycle cost analysis can be performed for

states other than Louisiana.

• In the future, individual EPDs for the State of Louisiana should be issued. This will

provide a more accurate comparison between products vs. the industry average EPD.

• Future research should also focus on integrating the social aspect, together with the

environmental and the economic criteria into the pavement design framework, whenever

the social models become more developed.

• Future work should focus on evaluating transportation cost; this study solely focused on

the environmental impact of transportation stage.

299

APPENDICES

300

APPENDIX A. INDIVIDUAL EPD COMPILATION

The units used for All EPDs are as follows:

Environmental

impact/inventory

Unit

GWP kg CO2-eq/yd3

ODP kg CFC-11-eq/yd3

AP kg SO2-eq/yd3

EP kg N-eq/yd3

POCP kg O3-eq/yd3

PEC MJ/yd3

NRE MJ/yd3

RE MJ/yd3

NRM kg/yd3

RM kg/yd3

CBW m3/yd3

CWW m3/yd3

TW m3/yd3

CHW kg/yd3

CNHW kg/yd3

Mix design properties Unit

Cement lb

Slag lb

Fly Ash lb

Fine Aggregate lb

Coarse Aggregate1 lb

Coarse Aggregate1 lb

Mixing_Water (Louisiana) gallons

Mixing_Water (all other states) lb

301

Mix design properties Unit

Water_Reducer oz

Set_Accelerator oz

Super_Placticizer oz

Special_Additive_A oz

Special_Additive_B oz

Special_Additive_C oz

Retarder oz

Total weight lb

Density lb/ft3

Mix design cost $/y3

Values are given per 1 yd3

302

Product

ID UNITS_OF_VOLUME COMPANY_NAME ZIP_CODE

COMPRESSIVE_

STRENGTH (PSI) GWP ODP

1597 yd3 Argos-Mesquite 75149 3000 264.55 3.05E-06

1734 yd3 Argos-Mesquite 75149 4500 288.25 3.31E-06

1735 yd3 Argos-Mesquite 75149 4000 312.72 3.56E-06

1738 yd3 Argos-Mesquite 75149 4400 305.83 3.51E-06

1811 yd3 Argos-Mesquite 75149 4500 259.96 2.99E-06

1841 yd3 Argos-Mesquite 75149 4500 336.42 3.82E-06

1899 yd3 Argos-Mesquite 75149 5000 360.88 4.08E-06

2554 yd3 Argos-Mesquite 75149 3000 265.31 3.07E-06

4070 yd3 Argos-Mesquite 75149 4500 201.85 2.38E-06

4072 yd3 Argos-Mesquite 75149 6000 231.67 2.69E-06

4176 yd3 Argos-Mesquite 75149 9000 430.46 4.92E-06

8482 yd3 Argos-Mesquite 75149 5000 318.83 3.66E-06

9279 yd3 Argos-Mesquite 75149 6000 385.35 4.47E-06

9630 yd3 Argos-Mesquite 75149 5000 360.88 4.10E-06

9908 yd3 Argos-Mesquite 75149 8000 409.82 4.71E-06

9920 yd3 Argos-Mesquite 75149 8000 383.06 4.43E-06

9930 yd3 Argos-Mesquite 75149 9000 404.47 4.62E-06

9932 yd3 Argos-Mesquite 75149 9000 405.23 4.67E-06

1597 yd3 Argos-Downtown Dallas 75212 4000 267.60 3.13E-06

1734 yd3 Argos-Downtown Dallas 75212 3000 290.54 3.39E-06

1735 yd3 Argos-Downtown Dallas 75212 4500 315.01 3.65E-06

1738 yd3 Argos-Downtown Dallas 75212 4000 308.89 3.59E-06

303

Product

ID UNITS_OF_VOLUME COMPANY_NAME ZIP_CODE

COMPRESSIVE_

STRENGTH (PSI) GWP ODP

1811 yd3 Argos-Downtown Dallas 75212 4400 262.25 3.07E-06

1841 yd3 Argos-Downtown Dallas 75212 4500 339.48 3.90E-06

1899 yd3 Argos-Downtown Dallas 75212 4500 363.18 4.16E-06

2554 yd3 Argos-Downtown Dallas 75212 5000 267.60 3.15E-06

4070 yd3 Argos-Downtown Dallas 75212 3000 204.14 2.46E-06

Product

ID

AP EP POCP TOTAL_PRIMARY_

ENERGY_CONSUMPTION

NON_RENEWABLE_

ENERGY_CONSUMPTION

RENEWABLE_PRIMARY_

ENERGY_CONSUMPTION

1597 1.49 0.05 21.56 1488.65 1477.94 11.14

1734 1.61 0.05 23.24 1602.57 1590.34 11.92

1735 1.73 0.05 24.70 1713.43 1701.20 12.52

1738 1.70 0.05 24.31 1685.91 1673.68 12.55

1811 1.47 0.05 21.64 1468.77 1458.06 10.76

1841 1.86 0.06 26.38 1827.36 1813.59 13.18

1899 1.98 0.06 27.91 1938.99 1925.22 13.92

2554 1.49 0.05 21.56 1494.00 1482.53 11.33

4070 1.18 0.04 18.20 1208.81 1200.40 9.14

4072 1.34 0.04 20.26 1349.49 1339.55 9.90

4176 2.34 0.07 32.42 2286.87 2270.82 16.37

8482 1.77 0.05 25.31 1749.37 1736.37 12.78

9279 2.11 0.06 29.44 2075.85 2060.56 15.07

9630 1.98 0.06 27.75 1941.28 1926.75 14.20

9908 2.23 0.06 31.04 2187.48 2172.18 15.75

304

9920 2.11 0.06 29.59 2067.44 2052.14 14.79

9930 2.22 0.06 31.04 2167.60 2152.31 15.35

9932 2.22 0.06 30.97 2171.42 2155.36 15.44

1597 1.50 0.05 21.41 1520.76 1510.05 11.16

1734 1.62 0.05 23.17 1635.45 1623.21 11.94

1735 1.75 0.05 24.62 1744.78 1731.78 12.55

1738 1.71 0.05 24.24 1719.55 1706.55 12.57

1811 1.48 0.05 21.48 1499.35 1488.65 10.77

1841 1.87 0.05 26.23 1857.18 1844.18 13.21

1899 1.99 0.06 27.75 1968.80 1955.04 13.95

2554 1.50 0.05 21.48 1526.88 1516.17 11.35

4070 1.19 0.04 18.04 1240.16 1230.98 9.14

Product ID NON_RENEWABLE_MATERIAL_

RESOURCES_CONSUMPTION

RENEWABLE_MATERIAL_

RESOURCES_CONSUMPTION

CONCRETE_BATCHING_

WATER_CONSUMPTION

CONCRETE_WASHING_

WATER_CONSUMPTION

1597 1477.94 0.48 0.11 0.05

1734 1590.34 0.52 0.12 0.05

1735 1701.20 0.56 0.12 0.05

1738 1673.68 0.55 0.12 0.05

1811 1458.06 0.47 0.12 0.05

1841 1813.59 0.59 0.12 0.05

1899 1925.22 0.63 0.12 0.05

2554 1482.53 0.49 0.12 0.05

4070 1200.40 0.39 0.10 0.05

4072 1339.55 0.43 0.11 0.05

305

Product ID NON_RENEWABLE_MATERIAL_

RESOURCES_CONSUMPTION

RENEWABLE_MATERIAL_

RESOURCES_CONSUMPTION

CONCRETE_BATCHING_

WATER_CONSUMPTION

CONCRETE_WASHING_

WATER_CONSUMPTION

4176 2270.82 0.73 0.12 0.05

8482 1736.37 0.56 0.13 0.05

9279 2060.56 0.66 0.11 0.05

9630 1926.75 0.63 0.13 0.05

9908 2172.18 0.70 0.12 0.05

9920 2052.14 0.66 0.12 0.05

9930 2152.31 0.69 0.12 0.05

9932 2155.36 0.69 0.13 0.05

1597 1834.24 0.47 0.11 0.05

1734 1888.52 0.51 0.12 0.05

1735 1844.94 0.54 0.12 0.05

1738 1899.23 0.53 0.12 0.05

1811 1818.95 0.46 0.12 0.05

1841 1849.53 0.58 0.12 0.05

1899 1857.94 0.61 0.12 0.05

2554 1886.23 0.47 0.12 0.05

4070 1885.47 0.38 0.10 0.05

Product_

ID

TOTAL_WATER_

CONSUMPTION CONCRETE_HAZARDOUS_WASTE CONCRETE_NON_HAZARDOUS_WASTE

Cement Weight

(lb)

1597 0.16 0.00 0.96 492.00

306

Product_

ID

TOTAL_WATER_

CONSUMPTION CONCRETE_HAZARDOUS_WASTE CONCRETE_NON_HAZARDOUS_WASTE

Cement Weight

(lb)

1734 0.17 0.00 0.96 411.00

1735 0.17 0.00 0.96 451.00

1738 0.17 0.00 0.96 441.00

1811 0.17 0.00 0.96 367.00

1841 0.17 0.00 0.96 489.00

1899 0.17 0.00 0.96 526.00

2554 0.16 0.00 0.96 376.00

4070 0.15 0.00 0.96 276.00

4072 0.16 0.00 0.96 322.00

4176 0.17 0.03 0.96 635.00

8482 0.18 0.00 0.96 461.00

9279 0.16 0.02 0.96 564.00

9630 0.18 0.00 0.96 526.00

9908 0.16 0.02 0.96 602.00

9920 0.17 0.03 0.96 559.00

9930 0.17 0.03 0.96 592.00

9932 0.17 0.03 0.96 595.00

1597 0.16 0.00 0.96 376.00

1734 0.17 0.00 0.96 411.00

1735 0.17 0.00 0.96 451.00

1738 0.17 0.00 0.96 441.00

1811 0.17 0.00 0.96 367.00

307

Product_

ID

TOTAL_WATER_

CONSUMPTION CONCRETE_HAZARDOUS_WASTE CONCRETE_NON_HAZARDOUS_WASTE

Cement Weight

(lb)

1841 0.17 0.00 0.96 489.00

1899 0.17 0.00 0.96 526.00

2554 0.16 0.00 0.96 376.00

4070 0.15 0.00 0.96 276.00

Product ID Water Cement

Ratio

Mixing Water

(lb)

Fly Ash

(lb)

Slag

(lb)

Fine

Aggregate

(lb)

Coarse

Aggregate (lb)

Total

Weight

(lb)

1597 0.50 246.00 118.00 0.00 1309.00 1875.00 3924.00

1734 0.45 262.00 176.00 0.00 1346.00 1840.00 4035.00

1735 0.43 257.00 141.00 0.00 1193.00 1875.00 3917.00

1738 0.44 261.00 147.00 0.00 1353.00 1840.00 4042.00

1811 0.42 254.00 244.00 0.00 1202.00 1840.00 3906.00

1841 0.41 263.00 153.00 0.00 1108.00 1900.00 3913.00

1899 0.39 267.00 165.00 0.00 1079.00 1875.00 3912.00

2554 0.53 249.00 94.00 0.00 1433.00 1900.00 4052.00

4070 0.43 242.00 288.00 0.00 1340.00 1900.00 4045.00

4072 0.36 240.00 336.00 0.00 1256.00 1900.00 4045.00

4176 0.31 260.00 212.00 0.00 1256.00 1750.00 4073.00

8482 0.42 275.00 197.00 0.00 1248.00 1840.00 4021.00

9279 0.35 250.00 141.00 0.00 1285.00 1840.00 4080.00

9630 0.42 275.00 132.00 0.00 1200.00 1900.00 4033.00

308

9908 0.33 251.00 150.00 0.00 1241.00 1840.00 4084.00

9920 0.32 259.00 240.00 0.00 1204.00 1800.00 4062.00

9930 0.31 262.00 254.00 0.00 1840.00 1840.00 4062.00

9932 0.32 273.00 255.00 0.00 1172.00 1750.00 4044.00

1597 0.50 246.00 118.00 0.00 1309.00 1875.00 3924.00

1734 0.45 262.00 176.00 0.00 1346.00 1840.00 4035.00

1735 0.43 257.00 141.00 0.00 1193.00 1875.00 3917.00

1738 0.44 261.00 147.00 0.00 1353.00 1840.00 4042.00

1811 0.42 254.00 244.00 0.00 1202.00 1840.00 3906.00

1841 0.41 263.00 153.00 0.00 1108.00 1900.00 3913.00

1899 0.39 267.00 165.00 0.00 1079.00 1875.00 3912.00

2554 0.53 249.00 94.00 0.00 1433.00 1900.00 4052.00

4070 0.43 242.00 288.00 0.00 1340.00 1900.00 4045.00

Product_ ID Price_

$/Y3 REGION STATE Validity

Slump

(Inch) Air Percent

1597 201.25 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

1734 206.25 South Texas August 26th, 2019 4.00 +/- 1.00 1.50 +/- 1.50

1735 206.30 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

1738 206.25 South Texas August 26th, 2019 4.00 +/- 1.00 1.50 +/- 1.50

1811 207.50 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

1841 208.80 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

1899 211.35 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

2554 198.75 South Texas August 26th, 2019 4.00 +/- 1.00 1.50 +/- 1.50

4070 208.00 South Texas August 26th, 2019 6.00 +/- 1.00 1.50 +/- 1.50

4072 212.00 South Texas August 26th, 2019 6.00 +/- 1.00 1.50 +/- 1.50

309

Product_ ID Price_

$/Y3 REGION STATE Validity

Slump

(Inch) Air Percent

4176 229.00 South Texas August 26th, 2019 7.50 +/- 1.00 1.50 +/- 1.50

8482 213.00 South Texas August 26th, 2019 6.00 +/- 1.00 1.50 +/- 1.50

9279 222.50 South Texas August 26th, 2019 7.50 +/- 1.00 1.50 +/- 1.50

9630 213.00 South Texas August 26th, 2019 6.00 +/- 1.00 1.50 +/- 1.50

9908 227.50 South Texas August 26th, 2019 7.50 +/- 1.00 1.50 +/- 1.50

9920 224.00 South Texas August 26th, 2019 7.50 +/- 1.00 1.50 +/- 1.50

9930 229.00 South Texas August 26th, 2019 7.50 +/- 1.00 1.50 +/- 1.50

9932 229.25 South Texas August 26th, 2019 7.50 +/- 1.00 1.50 +/- 1.50

1597 201.25 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

1734 206.25 South Texas August 26th, 2019 4.00 +/- 1.00 1.50 +/- 1.50

1735 206.30 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

1738 206.25 South Texas August 26th, 2019 4.00 +/- 1.00 1.50 +/- 1.50

1811 207.50 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

1841 208.80 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

1899 211.35 South Texas August 26th, 2019 4.00 +/- 1.00 4.50 +/- 1.50

2554 198.75 South Texas August 26th, 2019 4.00 +/- 1.00 1.50 +/- 1.50

4070 208.00 South Texas August 26th, 2019 6.00 +/- 1.00 1.50 +/- 1.50

310

APPENDIX B. INDUSTRY WIDE AVERAGE EPD COMPILATION

GWP ODP AP EP POCP PEC NRE RE NRM RM CBW CWW TW CHW CNHW

kg CO2 kg CFC-11 kg SO2 kg N kg O3 MJ MJ MJ kg kg m3 m3 m3 kg kg

2500 psi per yd3 220.14 5.61E-06 0.77 0.27 16.07 1,503.6 1,475.9 27.7 1,703.2 1.62 0.14 0.13 0.30 0.33 3.683000 psi per yd3 245.28 6.25E-06 0.84 0.30 17.38 1,642.6 1,611.9 30.8 1,709.1 1.80 0.14 0.13 0.29 0.33 3.904000 psi per yd3 300.30 7.63E-06 0.98 0.36 20.25 1,950.7 1,913.2 37.5 1,726.7 2.20 0.14 0.13 0.29 0.33 4.375000 psi per yd3 371.14 9.41E-06 1.17 0.44 23.91 2,347.6 2,301.5 46.1 1,723.4 2.71 0.14 0.13 0.30 0.34 4.976000 psi per yd3 391.09 9.91E-06 1.23 0.47 25.06 2,466.6 2,418.1 48.6 1,791.8 2.86 0.15 0.14 0.32 0.34 5.148000 psi per yd3 476.85 1.21E-05 1.46 0.57 29.51 2,950.1 2,891.1 59.0 1,808.2 3.48 0.15 0.14 0.32 0.34 5.873000 psi

Lightweig

per yd3 379.36 1.60E-05 1.69 0.50 24.94 3,223.2 3,183.8 39.4 1,407.6 8.50 0.14 0.13 0.52 0.33 3.924000 psi

Lightweig

per yd3 437.97 1.76E-05 1.85 0.57 28.01 3,572.7 3,526.4 46.4 1,415.9 9.05 0.14 0.13 0.53 0.33 4.395000 psi

Lightweig

per yd3 501.36 1.94E-05 2.03 0.64 31.33 3,951.3 3,897.3 53.9 1,425.3 9.63 0.14 0.13 0.53 0.34 4.91

Table E1-NRMCA U.S. National LCA ResultsIndicator/LCI

Metric Unit

GWP ODP AP EP POCP PEC NRE RE NRM RM CBW CWW TW CHW CNHW

kg CO2 kg CFC-11 kg SO2 kg N kg O3 MJ MJ MJ kg kg m3 m3 m3 kg kg

2500 psi per yd3 228.62 6.15E-06 0.82 0.28 16.53 1,593.3 1,563.4 29.9 1,731.1 1.73 0.14 0.12 0.30 0.02 2.823000 psi per yd3 254.96 6.85E-06 0.90 0.31 17.93 1,744.1 1,710.8 33.3 1,751.9 1.93 0.14 0.12 0.30 0.02 3.044000 psi per yd3 312.54 8.39E-06 1.06 0.38 21.00 2,077.2 2,036.5 40.7 1,799.8 2.35 0.14 0.12 0.30 0.03 3.525000 psi per yd3 385.60 1.03E-05 1.26 0.46 24.69 2,489.9 2,439.9 50.1 1,740.6 2.89 0.15 0.13 0.31 0.03 4.156000 psi per yd3 406.40 1.09E-05 1.32 0.49 25.89 2,616.8 2,564.1 52.7 1,810.5 3.05 0.16 0.14 0.33 0.04 4.328000 psi per yd3 495.57 1.32E-05 1.56 0.59 30.54 3,131.1 3,067.0 64.1 1,828.9 3.71 0.16 0.14 0.33 0.05 5.073000 psi

Lightweig

per yd3 391.71 1.69E-05 1.76 0.52 25.50 3,354.2 3,312.3 41.9 1,398.8 8.82 0.15 0.13 0.54 0.02 3.064000 psi

Lightweig

per yd3 452.40 1.87E-05 1.94 0.59 28.69 3,723.0 3,673.5 49.5 1,405.0 9.39 0.15 0.13 0.54 0.03 3.545000 psi

Lightweig

per yd3 517.98 2.05E-05 2.13 0.67 32.14 4,122.1 4,064.4 57.7 1,412.3 10.00 0.15 0.13 0.55 0.03 4.07

Table E2-Eastern LCA ResultsIndicator/LCI

Metric Unit

311

312

TW CHW CNHW

m3 kg kg

0.29 0.00 1.94

0.38 0.00 2.54

0.29 0.00 1.94

0.38 0.00 2.54

0.29 0.00 1.94

0.38 0.00 2.54

0.30 0.00 1.94

0.39 0.00 2.54

0.32 0.00 1.94

0.42 0.00 2.54

0.32 0.00 1.94

0.42 0.00 2.54

0.56 0.01 3.53

0.73 0.01 4.61

0.56 0.01 3.93

0.74 0.02 5.14

4000 psi

Lightweight

per yd3 397.04 1.67E-05 1.73 0.52 25.22 3,345.3 3,304.7 40.5 1,447.9 8.92 0.11 0.18

per m3 519.30 2.19E-05 2.27 0.69 32.99 4,375.4 4,322.4 53.0 1,893.8 11.67 0.15 0.23

3000 psi

Lightweight

per yd3 346.55 1.53E-05 1.59 0.46 22.52 3,040.7 3,006.1 34.6 1,437.6 8.44 0.11 0.18

per m3 453.27 2.01E-05 2.08 0.61 29.45 3,977.1 3,931.9 45.3 1,880.3 11.04 0.15 0.23

8000 psi per yd3 419.68 6.66E-06 2.31 0.35 27.97 3,202.4 3,180.0 22.3 1,857.8 0.62 0.13 0.20

per m3 548.92 8.71E-06 3.02 0.46 36.58 4,188.5 4,159.3 29.2 2,429.9 0.81 0.16 0.26

6000 psi per yd3 343.86 5.50E-06 2.01 0.30 24.62 2,660.5 2,641.8 18.7 1,826.5 0.54 0.13 0.20

per m3 449.76 7.19E-06 2.63 0.39 32.20 3,479.8 3,455.4 24.4 2,388.9 0.70 0.16 0.26

5000 psi per yd3 326.42 5.23E-06 1.94 0.29 23.76 2,530.6 2,512.8 17.8 1,761.1 0.51 0.12 0.18

per m3 426.94 6.84E-06 2.53 0.38 31.08 3,309.8 3,286.6 23.3 2,303.4 0.67 0.15 0.24

4000 psi per yd3 264.14 4.28E-06 1.13 0.21 14.92 2,087.2 2,072.4 14.8 1,747.7 0.45 0.11 0.18

per m3 345.49 5.59E-06 1.48 0.27 19.51 2,730.0 2,710.6 19.3 2,285.9 0.58 0.15 0.23

3000 psi per yd3 215.95 3.54E-06 0.94 0.17 12.79 1,745.0 1,732.5 12.5 1,725.0 0.39 0.11 0.18

per m3 282.45 4.63E-06 1.23 0.23 16.72 2,282.4 2,266.1 16.3 2,256.2 0.51 0.15 0.23

2500 psi per yd3 194.09 3.20E-06 0.86 0.16 11.83 1,591.9 1,580.5 11.4 1,723.5 0.37 0.11 0.18

per m3 253.86 4.19E-06 1.12 0.21 15.48 2,082.2 2,067.3 14.9 2,254.2 0.48 0.15 0.23

Table E4-North Central LCA Results

Indicator/LCI Metric Unit

(equivalent)

GWP ODP AP EP POCP PEC NRE RE NRM RM CBW CWW

kg CO2 kg CFC-11 kg SO2 kg N kg O3 MJ MJ MJ kg kg m3 m3

313

GWP ODP AP EP POCP PEC NRE RE NRM RM CBW CWW TW CHW CNHW

kg CO2 kg CFC-11 kg SO2 kg N kg O3 MJ MJ MJ kg kg m3 m3 m3 kg kg

2500 psi per yd3 204.00 5.12E-06 0.75 0.24 16.01 1,392.6 1,364.4 28.2 1,767.9 1.47 0.13 0.05 0.20 0.01 5.473000 psi per yd3 227.91 5.73E-06 0.82 0.27 17.46 1,527.6 1,496.4 31.2 1,771.2 1.65 0.13 0.05 0.20 0.02 5.674000 psi per yd3 280.38 7.06E-06 0.97 0.33 20.65 1,827.5 1,789.9 37.6 1,783.4 2.03 0.13 0.05 0.20 0.02 6.115000 psi per yd3 348.27 8.78E-06 1.17 0.41 24.77 2,217.5 2,171.5 46.0 1,787.3 2.52 0.13 0.05 0.20 0.02 6.686000 psi per yd3 367.01 9.26E-06 1.23 0.44 26.00 2,330.4 2,282.1 48.3 1,854.6 2.65 0.14 0.06 0.22 0.03 6.848000 psi per yd3 449.58 1.13E-05 1.48 0.53 31.02 2,807.1 2,748.7 58.4 1,877.7 3.25 0.14 0.06 0.22 0.03 7.533000 psi

Lightweig

per yd3 386.66 1.68E-05 1.80 0.51 26.77 3,356.9 3,313.9 43.0 1,436.5 9.05 0.13 0.05 0.46 0.02 5.774000 psi

Lightweig

per yd3 444.90 1.84E-05 1.98 0.58 30.29 3,711.5 3,661.5 50.1 1,449.1 9.59 0.13 0.05 0.46 0.02 6.245000 psi

Lightweig

per yd3 509.38 2.03E-05 2.19 0.66 34.19 4,113.1 4,055.3 57.8 1,460.3 10.24 0.13 0.05 0.47 0.03 6.74

Indicator/LCI

Metric Unit

Table E5-Pacific Northwest LCA Results

314

GWP ODP AP EP POCP PEC NRE RE NRM RM CBW CWW TW CHW CNHW

kg CO2 kg CFC-11 kg SO2 kg N kg O3 MJ MJ MJ kg kg m3 m3 m3 kg kg

2500 psi per yd3 216.92 3.39E-06 0.96 0.09 13.04 1,776.3 1,745.8 30.4 1,725.7 0.38 0.13 0.07 0.21 0.00 0.523000 psi per yd3 240.85 3.72E-06 1.05 0.10 13.95 1,939.3 1,905.7 33.6 1,732.1 0.40 0.13 0.07 0.21 0.00 0.524000 psi per yd3 293.19 4.45E-06 1.25 0.12 15.95 2,299.5 2,258.9 40.6 1,751.1 0.46 0.13 0.07 0.21 0.00 0.525000 psi per yd3 360.51 5.39E-06 2.07 0.17 24.61 2,762.8 2,713.3 49.5 1,749.3 0.52 0.14 0.08 0.21 0.00 0.526000 psi per yd3 379.73 5.67E-06 2.14 0.18 25.45 2,902.0 2,850.0 52.0 1,818.9 0.55 0.15 0.08 0.23 0.00 0.528000 psi per yd3 461.40 6.81E-06 2.45 0.20 28.58 3,468.3 3,405.5 62.8 1,851.4 0.63 0.15 0.08 0.23 0.00 0.523000 psi

Lightweig

per yd3 379.60 1.60E-05 1.69 0.49 24.74 3,253.8 3,213.0 40.7 1,417.4 8.52 0.13 0.07 0.47 0.01 2.384000 psi

Lightweig

per yd3 437.56 1.76E-05 1.85 0.56 27.67 3,596.6 3,549.1 47.5 1,426.9 9.06 0.13 0.07 0.47 0.02 2.855000 psi

Lightweig

per yd3 500.27 1.93E-05 2.02 0.64 30.86 3,968.1 3,913.2 54.9 1,437.7 9.63 0.13 0.07 0.48 0.02 3.36

Indicator/LCI

Metric Unit

Table E7-Rocky Mountains LCA Results

GWP ODP AP EP POCP PEC NRE RE NRM RM CBW CWW TW CHW CNHW

kg CO2 kg CFC-11 kg SO2 kg N kg O3 MJ MJ MJ kg kg m3 m3 m3 kg kg

2500 psi per yd3 195.56 4.88E-06 0.70 0.24 14.81 1,346.9 1,323.5 23.4 1,691.3 1.42 0.12 0.20 0.35 0.01 11.013000 psi per yd3 217.71 5.43E-06 0.76 0.26 15.99 1,468.4 1,442.4 26.1 1,707.2 1.58 0.12 0.20 0.35 0.01 11.204000 psi per yd3 265.88 6.62E-06 0.88 0.32 18.52 1,733.2 1,701.4 31.9 1,715.4 1.93 0.12 0.20 0.35 0.01 11.615000 psi per yd3 328.17 8.16E-06 1.05 0.39 21.80 2,078.8 2,039.4 39.4 1,728.3 2.37 0.12 0.21 0.36 0.02 12.156000 psi per yd3 345.78 8.60E-06 1.10 0.41 22.84 2,183.3 2,141.8 41.5 1,794.2 2.50 0.13 0.22 0.39 0.02 12.298000 psi per yd3 421.14 1.05E-05 1.30 0.50 26.83 2,603.8 2,553.3 50.5 1,824.4 3.04 0.13 0.22 0.38 0.02 12.943000 psi

Lightweig

per yd3 352.20 1.52E-05 1.61 0.46 23.58 3,047.1 3,012.5 34.6 1,434.5 8.28 0.12 0.20 0.58 0.01 11.224000 psi

Lightweig

per yd3 405.97 1.68E-05 1.77 0.53 26.43 3,375.2 3,334.3 40.8 1,444.0 8.85 0.12 0.20 0.58 0.01 11.655000 psi

Lightweig

per yd3 464.05 1.84E-05 1.94 0.60 29.52 3,729.4 3,681.8 47.6 1,454.9 9.45 0.12 0.20 0.59 0.02 12.11

Indicator/LCI

Metric Unit

Table E8-South Central LCA Results

315

APPENDIX C. SURVEY PERFOMED IN LOUISIANA AND ASSOCIATED

RESULTS

A survey was performed in Louisiana to evaluate whether any companies have

measured any lifecycle impact assessment for their products. Results revealed that only

companies participated in the industry wide average survey, since this process is very

expensive to perform. However, very few companies (five companies) participated in this

industry wide average EPD, showing a total of 18 plants. The sample was not statistically

representative, and the data had to be aggregated, together with other values in the south

central region.

The survey was prepared under the supervision of the Institutional Review Board (IRB) at

Louisiana State University, and is composed of the following sections:

• Project description: The first page described the project. Also, the link to the project

website was provided for details.

• A guide to consent form: This page gives contact information about the preparers, the

purpose of the research and data sensitivity, the study procedures, the risk involved in

participation, and the right to refuse to participate.

• Finally, the actual survey is provided.

316

A brief project description

The aim of this research is to provide the Louisiana Department of Transportation and

Development (DOTD) with a user-friendly decision making tool for quantifying the

sustainability of pavement designs.

To achieve this objective, this survey aims to collect data related to lifecycle environmental

impact and inventory data for concrete products produced in Louisiana. The collected data

will be integrated into the pavement Mechanistic-Empirical design framework, as a

sustainability input and the overall design will be evaluated based on performance,

environmental and economic criteria.

More information about the project can be found in this

website: http://www.ltrc.lsu.edu/pdf/2016/capsule_17-3P.pdf

317

Guide to Consent

1. Name and contact information of the investigator(s).

The researchers conducting this survey are:

Neveen Soliman. Please direct any questions you have to ntalaa1@lsu.edu

Co-investigator: Prof. Marwa Hassan

Contact information: marwa@lsu.edu

2. Purpose of the research and data sensitivity

The purpose of this research is to measure/assess lifecycle category indicators and

inventory metrics in Louisiana Plants producing concrete.

The answers to this survey might be sensitive. However, the data will be kept

confidential.

3. Study procedures.

To participate in this study: 1) your plant should be located in Louisiana, and 2) you

should be producing concrete.

You will be asked to fill in a survey about your concrete plant located in Louisiana.

The purpose is to collect data about lifecycle category indicators and inventory

metrics. If you performed these measurements, please provide them. If you did not

perform any of these measurements, please state the reason.

4. Risk involved in participation

There is no risk involved in this study except for data sensitivity. However, the data

will be kept confidential.

5. Inform the participants of their right to refuse.

“Subjects may choose not to participate or to withdraw from the study at any time

without penalty or loss of any benefit to which they might otherwise be entitled.”

318

Subjects may choose not to participate or to withdraw from the study at any time

without penalty or loss of any benefit to which they might otherwise be entitled.

The extent to which your privacy will be protected by the following procedures:

All your answers will be confidential. The answers for this study will be kept private.

If answers were made public, we will not reveal any information that will make it

possible to identify you.

“By continuing this survey, you are giving consent to participate in this study.”

Note: The Institutional Review Board (IRB) looked at the project and determined there

was no need for a formal review.

319

Section 1: General information

1. Please provide information about your company.

Company name

Company address

Street

City

State

Zip code

2. Please provide information about your plant, located in Louisiana.

Plant name

Plant address

City

State

Zip code

3. Please provide information about the preparer.

Name of the preparer

Position

Contact information

Section 2: Measurement

320

4. Please indicate if you measured the following lifecycle environmental impact

data/inventory metrics in your plant for the produced concrete mix designs.

Global Warming Potential

Acidification Potential

Eutrophication Potential

Ozone Depletion Potential

Photochemical Ozone Creation Potential

Total primary energy consumption

Depletion of non-renewable energy resources

Use of renewable primary energy

Depletion of non-renewable material resources

Use of renewable material resources

Concrete batching water consumption

Concrete washing water consumption

Total water consumption

Concrete hazardous waste

Concrete non-hazardous waste

None of the above

5. If the answer to the above is “none of the above.” Please indicate the reason.

The plant is small

321

Not required per regulation

All of the above

Other: Please indicate

If you answered any of the options in Question 4, please proceed to sections 3 and 4.

322

Section 3: Mix design properties

Please provide information about the mix designs produced in your plant and for which you

measured any of the options in Question 4.

323

Mix

Design

ID

Compressive

strength

value (psi)

Cement

(lb)

Fly

ash

(lb)

Slag

(lb)

Water/cement

ratio

Water

(lb)

Coarse

aggregate

(lb)

Fine

aggregate (lb)

Slump

Air

(%)

Nominal Maximum

aggregate size for

aggregate (inch)

324

Section 4: Lifecycle environmental impact data/inventory metrics

Please provide information about lifecycle environmental impact data/inventory metrics

measured for the mix designs in section 3.

325

Mix

Desig

n ID

Glo

bal W

armin

g P

oten

tial

Acid

ification P

oten

tial

Eutro

phicatio

n P

oten

tial

Ozo

ne D

epletio

n P

oten

tial

Photo

chem

ical Ozo

ne C

reation P

oten

tial

Total p

rimary

energ

y co

nsu

mp

tion

Dep

letion o

f non

-renew

able en

ergy reso

urces

Use o

f renew

able p

rimary

energ

y

Dep

letion o

f non

-renew

able m

aterial resou

rces

Use o

f renew

able m

aterial resources

Concrete b

atchin

g w

ater consu

mptio

n

Concrete w

ashin

g w

ater consu

mptio

n

Total w

ater consu

mptio

n

Concrete h

azardous w

aste

Concrete n

on

-hazard

ous w

aste

326

Section 5: Other information (optional). Please provide any information you find useful or

anything you want to add

327

APPENDIX D. RESULTS OF LOUISIANA SURVEY AND DEVELOPED EPD

FOR LOUISIANA

Based on the accomplished survey, the following are the companies/plants that participated in

the industry wide EPD. As illustrated, there are five companies with a total of sixteen plants.

Count Company Plant Name

1 Angelle Concrete Group, LLC Denham Springs

2 Angelle Concrete Group, LLC Westport

3 Angelle Concrete Group, LLC Zachary

4 Builders Supply Co., Inc. Forth Street Plant

5 Builders Supply Co., Inc. Minden Plant

6 Builders Supply Co., Inc. Natchitoches Plant

7 Builders Supply Co., Inc. St. Vincent Plant

8 Builders Supply Co., Inc. Viking Dr. Plant

9 Dolese Bros. Co. South Choctaw Batch Baton Rouge Louisiana Plant

10 Lafarge North America Plant 30408-Airport

11 Lafarge North America Plant 30442-Gramercy

12 Lafarge North America Plant 30453-Houma

13 Martin Marietta Cheniere

14 Martin Marietta Jonesville

15 Martin Marietta Monroe B

16 Martin Marietta West Monroe

The mix designs had the following format/headings: cement, fly ash, slag, coarse aggregate 1,

coarse aggregate 2, water, water reducer, air, air entertainer, set accelerator, super plasticizer,

special additives (A), special additive (B) and special additive (C). The sources/ types of each

material is illustrated.

Material Type

Cement Type 1 or Type 2

Fly ash Class C

Slag None of the selected mixes contain

slag

Fine aggregate Fine Aggregate (concrete sand)

Coarse aggregate1 Grade A coarse aggregate (Stone)

for concrete and Grade A coarse

aggregate (gravel) for concrete

Coarse aggregate 2 Grade F and Grade A coarse

aggregate (stone aggregate)

328

Sample of the EPD created for Louisiana, company names were omitted.

No Class Type Construction Type Compressive strength Cement Weight Fly Ash Slag Fine Coarse Aggregate1

1 B PCC Pavement 6580 414 103 0 1180 1481

2 E PCC Pavement 5240 752 0 0 1259 1790

3 B PCC Pavement 4800 455 80 0 1439 1409

4 B PCC Pavement 4800 455 80 0 1439 1409

5 B PCC Pavement 4800 479 85 0 1378 1351

6 E PCC Pavement 5240 705 0 0 1297 1273

7 B PCC Pavement 4730 380 95 0 1430 1515

8 B PCC Pavement 4730 475 0 0 1441 1527

9 B PCC Pavement 4800 455 80 0 1439 1409

10 B PCC Pavement 6580 414 103 0 1291 1559

11 B PCC Pavement 4970 475 0 0 993 2006

12 E PCC Pavement 5240 880 0 0 1074 1975

13 B PCC Pavement 6580 414 103 0 1092 1353

14 B PCC Pavement 4800 475 0 0 1570 1570

15 B PCC Pavement 5120 468 83 0 1510 1325

16 B PCC Pavement 6470 420 105 0 1267 1272

17 B PCC Pavement 6470 420 105 0 1236 1538

18 E PCC Pavement 4400 658 0 0 1345 1810

19 E PCC Pavement 4400 510 100 0 1354 1866

20 E PCC Pavement 4400 550 61 0 1365 1857

21 B PCC Pavement 5100 414 103 0 1285 1379

22 B PCC Pavement 5100 420 105 0 1256 1230

23 B PCC Pavement 5100 414 103 0 1281 1376

329

No Class Type Construction Type Compressive strength Cement Weight Fly Ash Slag Fine Coarse Aggregate1

24 B PCC Pavement 6470 400 70 0 1389 1945

25 B PCC Pavement 6490 420 105 0 1256 1230

26 E PCC Pavement 5240 455 80 0 1439 1409

27 B PCC Pavement 5540 413 104 0 1483 1421

28 E PCC Pavement 5300 600 0 0 1411 1850

29 B PCC Pavement 4800 414 103 0 1399 1652

30 B PCC Pavement 5455 455 80 0 1439 1409

31 B PCC Pavement 4720 488 122 0 1498 1230

32 B PCC Pavement 4720 408 102 0 1466 1628

No

Coarse Aggregate

2

Mixing

Water

Water cement

ratio

Water

Reducer

Air

Percent

Air

Entertainer

Set

Accelerator

Super

Plasticizer

Special

Additive A

1 413 29.6 0.6 20.7 5±2 2.1 0 0 0

2 0 31.6 0.35 30.1 5±2 0 0 0 0

3 213 28 0.51 20 5±2 4.5 0 0 0

4 213 28 0.51 20 5±2 0 0 0 0

5 479 30 0.52 17.4 5±2 0 0 0 0

6 451 33.8 0.4 21.8 5±2 0 0 0 0

7 152 27.3 0.6 23.8 5±2 2.4 0 0 0

8 153 27.3 0.48 33.3 5±2 2.3 0 0 0

9 213 28 0.51 21 5±2 4.5 0 0 0

10 413 31 0.62 20.7 5±2 0 0 0 0

11 0 27.3 0.48 0 5±2 5 0 0 0

12 0 25 0.24 0 5±2 0 640 80 0

13 846 30.3 0.61 15.51 5±2 0 0 0 0

14 0 26.9 0.47 16 5±2 3.6 0 0 0

330

No

Coarse Aggregate

2

Mixing

Water

Water cement

ratio

Water

Reducer

Air

Percent

Air

Entertainer

Set

Accelerator

Super

Plasticizer

Special

Additive A

15 210 29.5 0.53 20.8 5±2 2 0 0 0

16 430 30.1 0.6 15.75 5±2 5 0 0 0

17 240 15.75 0.31 0 5±2 5 0 0 0

18 0 30 0.38 0 5±2 0 0 0 19.74

19 0 28 0.46 20 5±2 0 0 0 0

20 0 28 0.42 66 5±2 0 0 0 0

21 607 31 0.62 20.7 5±2 0 0 0 0

22 605 29 0.58 21 5±2 0 0 0 0

23 604 31 0.62 20.7 5±2 0 0 0 0

24 0 28 0.58 14 5±2 0 0 0 0

25 605 29 0.58 21 5±2 3 0 0 0

26 210 28.8 0.53 20 5±2 4.5 0 0 0

27 320 31 0.63 15.51 5±2 0 0 0 0

28 0 27.3 0.38 0 5±2 0 0 52.6 0

29 0 30 0.6 20.68 5±2 2.01 0 0 0

30 210 28 0.51 20 5±2 4.5 0 0 0

31 400 32.2 0.55 30.5 5±2 0 0 0 0

32 163 30.5 0.62 15.3 5±2 0 0 0 0

1 0.00 0.00 0.00 3839.59 144.52 187.02 23.34 7.20 194.22

2 0.00 0.00 0.00 4066.74 145.16 335.01 27.39 7.20 342.20

3 0.00 0.00 0.00 3831.33 145.36 204.84 24.07 7.20 212.03

4 0.00 0.00 0.00 3831.05 145.35 204.82 24.06 7.20 212.02

5 0.00 0.00 0.00 4023.59 145.49 215.63 25.04 7.20 222.82

6 0.00 0.00 0.00 4009.59 144.40 314.29 26.55 7.20 321.48

7 0.00 0.00 0.00 3801.59 144.88 172.10 23.20 7.20 179.29

8 0.00 0.00 0.00 3826.18 144.62 213.82 23.45 7.20 221.01

331

No

Coarse Aggregate

2

Mixing

Water

Water cement

ratio

Water

Reducer

Air

Percent

Air

Entertainer

Set

Accelerator

Super

Plasticizer

Special

Additive A

9 0.00 0.00 0.00 3831.39 145.28 204.85 24.07 7.20 212.04

10 0.00 0.00 0.00 4040.14 144.50 187.34 24.32 7.20 194.54

11 0.00 0.00 0.00 3702.27 146.92 213.51 22.11 7.20 220.70

12 0.00 0.00 0.00 4182.75 153.41 422.52 30.28 7.20 429.71

13 0.00 0.00 0.00 4061.97 145.53 187.44 24.08 7.20 194.64

14 0.00 0.00 0.00 3840.84 146.07 213.66 23.73 7.20 220.85

15 0.00 0.00 0.00 3843.75 144.63 210.46 24.38 7.20 217.66

16 0.00 0.00 0.00 3746.63 144.31 189.37 23.18 7.20 196.57

17 0.00 0.00 0.00 3670.83 153.20 189.35 23.29 7.20 196.54

18 0.00 0.00 0.00 4064.73 147.60 293.77 26.39 7.20 300.97

19 0.00 0.00 0.00 4065.05 146.43 229.26 25.79 7.20 236.45

20 0.00 0.00 0.00 4070.93 143.31 247.15 25.96 7.20 254.35

21 0.00 0.00 0.00 4048.14 144.61 187.36 24.35 7.20 194.56

22 0.00 0.00 0.00 3859.46 144.95 189.65 23.67 7.20 196.84

23 0.00 0.00 0.00 4038.14 144.57 187.34 24.30 7.20 194.54

24 0.00 0.00 0.00 4038.68 146.09 181.25 24.05 7.20 188.45

25 0.00 0.00 0.00 3859.65 144.96 189.66 23.68 7.20 196.85

26 0.00 0.00 0.00 3835.01 144.97 204.83 24.06 7.20 212.03

27 0.00 0.00 0.00 4000.82 144.62 186.70 24.48 7.20 193.89

28 0.00 0.00 0.00 4092.24 148.74 270.03 26.07 7.20 277.22

29 0.00 0.00 0.00 3819.92 143.98 186.88 23.63 7.20 194.08

30 0.00 0.00 0.00 3828.33 145.35 204.83 24.06 7.20 212.03

31 0.00 0.00 0.00 4008.78 143.47 219.46 25.65 7.20 226.66

32 0.00 0.00 0.00 4022.63 144.87 184.58 24.48 7.20 191.77

No Special Additive B Special Additive C Retarder Mass Density GWP_A1 GWP_A2 GWP_A3 GWP Total

332

No Special Additive B Special Additive C Retarder Mass Density GWP_A1 GWP_A2 GWP_A3 GWP Total

1 0.00 0.00 0.00 3839.59 144.52 187.02 23.34 7.20 194.22

2 0.00 0.00 0.00 4066.74 145.16 335.01 27.39 7.20 342.20

3 0.00 0.00 0.00 3831.33 145.36 204.84 24.07 7.20 212.03

4 0.00 0.00 0.00 3831.05 145.35 204.82 24.06 7.20 212.02

5 0.00 0.00 0.00 4023.59 145.49 215.63 25.04 7.20 222.82

6 0.00 0.00 0.00 4009.59 144.40 314.29 26.55 7.20 321.48

7 0.00 0.00 0.00 3801.59 144.88 172.10 23.20 7.20 179.29

8 0.00 0.00 0.00 3826.18 144.62 213.82 23.45 7.20 221.01

9 0.00 0.00 0.00 3831.39 145.28 204.85 24.07 7.20 212.04

10 0.00 0.00 0.00 4040.14 144.50 187.34 24.32 7.20 194.54

11 0.00 0.00 0.00 3702.27 146.92 213.51 22.11 7.20 220.70

12 0.00 0.00 0.00 4182.75 153.41 422.52 30.28 7.20 429.71

13 0.00 0.00 0.00 4061.97 145.53 187.44 24.08 7.20 194.64

14 0.00 0.00 0.00 3840.84 146.07 213.66 23.73 7.20 220.85

15 0.00 0.00 0.00 3843.75 144.63 210.46 24.38 7.20 217.66

16 0.00 0.00 0.00 3746.63 144.31 189.37 23.18 7.20 196.57

17 0.00 0.00 0.00 3670.83 153.20 189.35 23.29 7.20 196.54

18 0.00 0.00 0.00 4064.73 147.60 293.77 26.39 7.20 300.97

19 0.00 0.00 0.00 4065.05 146.43 229.26 25.79 7.20 236.45

20 0.00 0.00 0.00 4070.93 143.31 247.15 25.96 7.20 254.35

21 0.00 0.00 0.00 4048.14 144.61 187.36 24.35 7.20 194.56

22 0.00 0.00 0.00 3859.46 144.95 189.65 23.67 7.20 196.84

23 0.00 0.00 0.00 4038.14 144.57 187.34 24.30 7.20 194.54

24 0.00 0.00 0.00 4038.68 146.09 181.25 24.05 7.20 188.45

25 0.00 0.00 0.00 3859.65 144.96 189.66 23.68 7.20 196.85

333

No Special Additive B Special Additive C Retarder Mass Density GWP_A1 GWP_A2 GWP_A3 GWP Total

26 0.00 0.00 0.00 3835.01 144.97 204.83 24.06 7.20 212.03

27 0.00 0.00 0.00 4000.82 144.62 186.70 24.48 7.20 193.89

28 0.00 0.00 0.00 4092.24 148.74 270.03 26.07 7.20 277.22

29 0.00 0.00 0.00 3819.92 143.98 186.88 23.63 7.20 194.08

30 0.00 0.00 0.00 3828.33 145.35 204.83 24.06 7.20 212.03

31 0.00 0.00 0.00 4008.78 143.47 219.46 25.65 7.20 226.66

32 0.00 0.00 0.00 4022.63 144.87 184.58 24.48 7.20 191.77

No ODP_A1 ODP_A2 ODP_A3 ODP_Total AP_A1 AP_A2 AP_A3

1 2.25758E-06 8.87589E-10 5.18306E-07 2.77588E-06 0.76 0.16 0.05

2 3.79463E-06 1.04156E-09 5.18306E-07 4.31293E-06 1.34 0.2 0.05

3 2.43698E-06 9.15217E-10 5.18306E-07 2.95529E-06 0.83 0.17 0.05

4 2.4369E-06 9.14921E-10 5.18306E-07 2.95521E-06 0.83 0.17 0.05

5 2.56677E-06 9.5201E-10 5.18306E-07 3.08507E-06 0.87 0.18 0.05

6 3.57569E-06 1.00964E-09 5.18306E-07 4.094E-06 1.26 0.19 0.05

7 2.0996E-06 8.82114E-10 5.18306E-07 2.61791E-06 0.7 0.16 0.05

8 2.53588E-06 8.91783E-10 5.18306E-07 3.05418E-06 0.86 0.16 0.05

9 2.43698E-06 9.15281E-10 5.18306E-07 2.95529E-06 0.83 0.17 0.05

10 2.27931E-06 9.24861E-10 5.18306E-07 2.79762E-06 0.76 0.17 0.05

11 2.53064E-06 8.40697E-10 5.18306E-07 3.04894E-06 0.86 0.16 0.05

12 4.44851E-06 1.15129E-09 5.18306E-07 4.96681E-06 1.69 0.22 0.05

13 2.28755E-06 9.15764E-10 5.18306E-07 2.80586E-06 0.76 0.17 0.05

14 2.53535E-06 9.02352E-10 5.18306E-07 3.05365E-06 0.86 0.17 0.05

15 2.49254E-06 9.27164E-10 5.18306E-07 3.01084E-06 0.85 0.17 0.05

16 2.26945E-06 8.81475E-10 5.18306E-07 2.78776E-06 0.76 0.16 0.05

17 2.27597E-06 8.85564E-10 5.18306E-07 2.79428E-06 0.76 0.16 0.05

18 3.3774E-06 1.00327E-09 5.18306E-07 3.89571E-06 1.18 0.19 0.05

334

No ODP_A1 ODP_A2 ODP_A3 ODP_Total AP_A1 AP_A2 AP_A3

19 2.71031E-06 9.80614E-10 5.18306E-07 3.22862E-06 0.92 0.18 0.05

20 2.89281E-06 9.87079E-10 5.18306E-07 3.41112E-06 0.99 0.18 0.05

21 2.28048E-06 9.25734E-10 5.18306E-07 2.79879E-06 0.76 0.17 0.05

22 2.28534E-06 9.0014E-10 5.18306E-07 2.80364E-06 0.77 0.17 0.05

23 2.27929E-06 9.23879E-10 5.18306E-07 2.79759E-06 0.76 0.17 0.05

24 2.2223E-06 9.14332E-10 5.18306E-07 2.74061E-06 0.73 0.17 0.05

25 2.28539E-06 9.00337E-10 5.18306E-07 2.8037E-06 0.77 0.17 0.05

26 2.43659E-06 9.1474E-10 5.18306E-07 2.9549E-06 0.83 0.17 0.05

27 2.26525E-06 9.31035E-10 5.18306E-07 2.78356E-06 0.76 0.17 0.05

28 3.13113E-06 9.91406E-10 5.18306E-07 3.64944E-06 1.09 0.19 0.05

29 2.24952E-06 8.9847E-10 5.18306E-07 2.76782E-06 0.75 0.16 0.05

30 2.43659E-06 9.1474E-10 5.18306E-07 2.9549E-06 0.83 0.17 0.05

31 2.59473E-06 9.75177E-10 5.18306E-07 3.11303E-06 0.88 0.18 0.05

32 2.24709E-06 9.30844E-10 5.18306E-07 2.7654E-06 0.75 0.17 0.05

No AP_Total EP_A1 EP_A2 EP_A3 EP_Total POCP_A1 POCP_A2 POCP_A3 POCP_Total PEC_A1 PEC_A2

1 0.8 0.08 0.01 0.01 0.09 12.93 4.63 0.22 13.15 1438.42 320.07

2 1.38 0.14 0.01 0.01 0.15 22.82 5.68 0.22 23.04 2525.54 375.59

3 0.87 0.09 0.01 0.01 0.1 14.12 4.8 0.22 14.34 1567.5 330.03

4 0.87 0.09 0.01 0.01 0.1 14.12 4.79 0.22 14.33 1567.16 329.93

5 0.92 0.09 0.01 0.01 0.1 14.86 5 0.22 15.08 1649.94 343.3

6 1.3 0.14 0.01 0.01 0.14 21.43 5.48 0.22 21.65 2371.56 364.08

7 0.74 0.08 0.01 0.01 0.08 11.93 4.57 0.22 12.15 1328.11 318.1

8 0.91 0.09 0.01 0.01 0.1 14.72 4.68 0.22 14.94 1636.11 321.58

335

No AP_Total EP_A1 EP_A2 EP_A3 EP_Total POCP_A1 POCP_A2 POCP_A3 POCP_Total PEC_A1 PEC_A2

9 0.87 0.09 0.01 0.01 0.1 14.12 4.8 0.22 14.34 1567.67 330.06

10 0.8 0.08 0.01 0.01 0.09 12.97 4.81 0.22 13.19 1444.23 333.51

11 0.91 0.09 0.01 0.01 0.1 14.69 4.44 0.22 14.91 1630.37 303.16

12 1.74 0.19 0.01 0.01 0.2 28.15 6.33 0.22 28.37 3518 415.16

13 0.81 0.08 0.01 0.01 0.09 12.98 4.76 0.22 13.2 1446.24 330.23

14 0.91 0.09 0.01 0.01 0.1 14.72 4.73 0.22 14.94 1632.82 325.39

15 0.89 0.09 0.01 0.01 0.1 14.49 4.87 0.22 14.71 1608.02 334.34

16 0.81 0.08 0.01 0.01 0.09 13.07 4.61 0.22 13.29 1452.42 317.87

17 0.81 0.08 0.01 0.01 0.09 13.08 4.63 0.22 13.29 1451.74 319.34

18 1.22 0.13 0.01 0.01 0.13 20.08 5.4 0.22 20.3 2221.23 361.79

19 0.97 0.1 0.01 0.01 0.11 15.77 5.17 0.22 15.99 1750.78 353.62

20 1.04 0.11 0.01 0.01 0.11 16.97 5.23 0.22 17.18 1887.13 355.95

21 0.8 0.08 0.01 0.01 0.09 12.98 4.81 0.22 13.19 1444.58 333.83

22 0.81 0.08 0.01 0.01 0.09 13.1 4.7 0.22 13.32 1457.54 324.6

23 0.8 0.08 0.01 0.01 0.09 12.97 4.8 0.22 13.19 1444.25 333.16

24 0.78 0.08 0.01 0.01 0.09 12.58 4.73 0.22 12.8 1399.79 329.71

25 0.81 0.08 0.01 0.01 0.09 13.1 4.7 0.22 13.32 1457.77 324.67

26 0.87 0.09 0.01 0.01 0.1 14.12 4.79 0.22 14.34 1567.39 329.86

27 0.8 0.08 0.01 0.01 0.09 12.93 4.83 0.22 13.15 1436.92 335.74

28 1.14 0.12 0.01 0.01 0.12 18.58 5.28 0.22 18.8 2072.97 357.51

29 0.8 0.08 0.01 0.01 0.09 12.91 4.68 0.22 13.13 1435.53 323.99

30 0.87 0.09 0.01 0.01 0.1 14.12 4.79 0.22 14.34 1567.39 329.86

31 0.93 0.1 0.01 0.01 0.1 15.1 5.13 0.22 15.32 1677.01 351.66

32 0.79 0.08 0.01 0.01 0.09 12.79 4.83 0.22 13.01 1422.18 335.67

336

No PEC_A3 PEC_Total NRE_A1 NRE_A2 NRE_A3 NRE_Total RE_A1 RE_A2 RE_A3 RE_Total NRM_A1 NRM_A2

1 121.34 1559.76 1288.68 320.07 113.39 1402.07 149.74 0 7.95 157.69 1778 0

2 121.34 2646.88 2261.11 375.59 113.39 2374.5 264.43 0 7.95 272.38 2000.32 0

3 121.34 1688.84 1404.19 330.03 113.39 1517.58 163.32 0 7.95 171.27 1800.05 0

4 121.34 1688.5 1403.84 329.93 113.39 1517.23 163.32 0 7.95 171.27 1800.05 0

5 121.34 1771.28 1477.9 343.3 113.39 1591.29 172.05 0 7.95 179.99 1888.03 0

6 121.34 2492.9 2123.25 364.08 113.39 2236.64 248.32 0 7.95 256.27 1954.12 0

7 121.34 1449.45 1190.15 318.1 113.39 1303.55 137.96 0 7.95 145.91 1765.49 0

8 121.34 1757.45 1465.79 321.58 113.39 1579.18 170.32 0 7.95 178.26 1843.03 0

9 121.34 1689.01 1404.35 330.06 113.39 1517.74 163.32 0 7.95 171.27 1800.05 0

10 121.34 1565.57 1293.98 333.51 113.39 1407.38 150.25 0 7.95 158.19 1869.65 0

11 121.34 1751.71 1459.94 303.16 113.39 1573.33 170.44 0 7.95 178.39 1784 0

12 121.34 3639.34 3209.85 415.16 113.39 3323.24 308.16 0 7.95 316.1 2089.18 0

13 121.34 1567.58 1295.66 330.23 113.39 1409.06 150.58 0 7.95 158.53 1883.31 0

14 121.34 1754.16 1462.59 325.39 113.39 1575.98 170.23 0 7.95 178.17 1852.2 0

15 121.34 1729.36 1440.42 334.34 113.39 1553.81 167.6 0 7.95 175.54 1801.28 0

16 121.34 1573.76 1301.1 317.87 113.39 1414.5 151.32 0 7.95 159.26 1731.2 0

17 121.34 1573.08 1300.23 319.34 113.39 1413.62 151.51 0 7.95 159.45 1753.04 0

18 121.34 2342.57 1988.49 361.79 113.39 2101.88 232.74 0 7.95 240.69 1986.5 0

19 121.34 1872.12 1568.12 353.62 113.39 1681.52 182.65 0 7.95 190.6 1915.36 0

20 121.34 2008.47 1690.89 355.95 113.39 1804.28 196.24 0 7.95 204.19 1944.08 0

21 121.34 1565.92 1294.3 333.83 113.39 1407.69 150.28 0 7.95 158.23 1873.53 0

22 121.34 1578.88 1305.79 324.6 113.39 1419.19 151.74 0 7.95 159.69 1790.39 0

23 121.34 1565.59 1294 333.16 113.39 1407.39 150.25 0 7.95 158.2 1868.68 0

24 121.34 1521.13 1254.18 329.71 113.39 1367.57 145.61 0 7.95 153.56 1894.35 0

25 121.34 1579.11 1306.02 324.67 113.39 1419.41 151.74 0 7.95 159.69 1790.39 0

337

No PEC_A3 PEC_Total NRE_A1 NRE_A2 NRE_A3 NRE_Total RE_A1 RE_A2 RE_A3 RE_Total NRM_A1 NRM_A2

26 121.34 1688.73 1404.08 329.86 113.39 1517.48 163.31 0 7.95 171.25 1798.59 0

27 121.34 1558.26 1287.38 335.74 113.39 1400.77 149.54 0 7.95 157.49 1849.97 0

28 121.34 2194.31 1859.66 357.51 113.39 1973.05 213.31 0 7.95 221.26 1997.67 0

29 121.34 1556.87 1286.13 323.99 113.39 1399.52 149.4 0 7.95 157.34 1766.77 0

30 121.34 1688.73 1404.08 329.86 113.39 1517.48 163.31 0 7.95 171.25 1798.59 0

31 121.34 1798.35 1502.32 351.66 113.39 1615.72 174.69 0 7.95 182.64 1855.42 0

32 121.34 1543.52 1274.2 335.67 113.39 1387.59 147.98 0 7.95 155.93 1862.52 0

No NRM_A3 NRM_Total RM_A1 RM_A2 RM_A3 RM_Total CBW_A1 CBW_A2 CBW_A3 CBW_Total

1 0.57 1778.58 4.95 0 0.1 5.05 0 0 0.12 0.12

2 0.57 2000.89 8.88 0 0.1 8.98 0 0 0.12 0.12

3 0.57 1800.62 5.42 0 0.1 5.52 0 0 0.11 0.11

4 0.57 1800.62 5.42 0 0.1 5.52 0 0 0.11 0.11

5 0.57 1888.6 5.71 0 0.1 5.81 0 0 0.12 0.12

6 0.57 1954.69 8.33 0 0.1 8.43 0 0 0.13 0.13

7 0.57 1766.06 4.55 0 0.1 4.65 0 0 0.11 0.11

8 0.57 1843.6 5.66 0 0.1 5.76 0 0 0.11 0.11

9 0.57 1800.62 5.42 0 0.1 5.52 0 0 0.11 0.11

10 0.57 1870.22 4.95 0 0.1 5.06 0 0 0.12 0.12

11 0.57 1784.58 5.66 0 0.1 5.76 0 0 0.11 0.11

12 0.57 2089.75 10.37 0 0.1 10.47 0 0 0.1 0.1

13 0.57 1883.88 4.96 0 0.1 5.06 0 0 0.12 0.12

14 0.57 1852.77 5.65 0 0.1 5.76 0 0 0.1 0.1

15 0.57 1801.85 5.57 0 0.1 5.67 0 0 0.11 0.11

16 0.57 1731.77 5.01 0 0.1 5.11 0 0 0.12 0.12

338

17 0.57 1753.61 5.01 0 0.1 5.12 0 0 0.06 0.06

18 0.57 1987.07 7.79 0 0.1 7.89 0 0 0.12 0.12

19 0.57 1915.94 6.07 0 0.1 6.17 0 0 0.11 0.11

20 0.57 1944.65 6.53 0 0.1 6.64 0 0 0.11 0.11

21 0.57 1874.11 4.95 0 0.1 5.06 0 0 0.12 0.12

22 0.57 1790.96 5.02 0 0.1 5.12 0 0 0.11 0.11

23 0.57 1869.26 4.95 0 0.1 5.06 0 0 0.12 0.12

24 0.57 1894.92 4.79 0 0.1 4.9 0 0 0.11 0.11

25 0.57 1790.96 5.02 0 0.1 5.12 0 0 0.11 0.11

26 0.57 1799.17 5.42 0 0.1 5.52 0 0 0.11 0.11

27 0.57 1850.54 4.94 0 0.1 5.04 0 0 0.12 0.12

28 0.57 1998.24 7.12 0 0.1 7.22 0 0 0.11 0.11

29 0.57 1767.34 4.94 0 0.1 5.04 0 0 0.12 0.12

30 0.57 1799.17 5.42 0 0.1 5.52 0 0 0.11 0.11

31 0.57 1855.99 5.81 0 0.1 5.91 0 0 0.13 0.13

32 0.57 1863.09 4.88 0 0.1 4.98 0 0 0.12 0.12

No CWW_A1 CWW_A2 CWW_A3 CWW_Total TW_A1 TW_A2 TW_A3 TW_Total CHW_A1 CHW_A2 CHW_A3

1 0 0 0.11 0.11 0.51 0 0.22 0.74 0.02 0 0.64

2 0 0 0.11 0.11 0.8 0 0.23 1.03 0.03 0 0.64

3 0 0 0.11 0.11 0.54 0 0.22 0.76 0.02 0 0.64

4 0 0 0.11 0.11 0.54 0 0.22 0.76 0.02 0 0.64

5 0 0 0.11 0.11 0.57 0 0.23 0.8 0.02 0 0.64

6 0 0 0.11 0.11 0.77 0 0.24 1.01 0.03 0 0.64

7 0 0 0.11 0.11 0.47 0 0.22 0.69 0.02 0 0.64

8 0 0 0.11 0.11 0.55 0 0.22 0.77 0.02 0 0.64

339

No CWW_A1 CWW_A2 CWW_A3 CWW_Total TW_A1 TW_A2 TW_A3 TW_Total CHW_A1 CHW_A2 CHW_A3

9 0 0 0.11 0.11 0.54 0 0.22 0.76 0.02 0 0.64

10 0 0 0.11 0.11 0.52 0 0.23 0.75 0.02 0 0.64

11 0 0 0.11 0.11 0.55 0 0.22 0.77 0.02 0 0.64

12 0 0 0.11 0.11 0.88 0 0.21 1.09 0.04 0 0.64

13 0 0 0.11 0.11 0.52 0 0.23 0.75 0.02 0 0.64

14 0 0 0.11 0.11 0.55 0 0.21 0.77 0.02 0 0.64

15 0 0 0.11 0.11 0.56 0 0.22 0.78 0.02 0 0.64

16 0 0 0.11 0.11 0.52 0 0.23 0.74 0.02 0 0.64

17 0 0 0.11 0.11 0.46 0 0.17 0.63 0.02 0 0.64

18 0 0 0.11 0.11 0.72 0 0.23 0.95 0.03 0 0.64

19 0 0 0.11 0.11 0.59 0 0.22 0.81 0.02 0 0.64

20 0 0 0.11 0.11 0.62 0 0.22 0.84 0.02 0 0.64

21 0 0 0.11 0.11 0.52 0 0.23 0.75 0.02 0 0.64

22 0 0 0.11 0.11 0.52 0 0.22 0.74 0.02 0 0.64

23 0 0 0.11 0.11 0.52 0 0.23 0.75 0.02 0 0.64

24 0 0 0.11 0.11 0.5 0 0.22 0.72 0.02 0 0.64

25 0 0 0.11 0.11 0.52 0 0.22 0.74 0.02 0 0.64

26 0 0 0.11 0.11 0.54 0 0.22 0.76 0.02 0 0.64

27 0 0 0.11 0.11 0.52 0 0.23 0.75 0.02 0 0.64

28 0 0 0.11 0.11 0.66 0 0.22 0.88 0.03 0 0.64

29 0 0 0.11 0.11 0.51 0 0.23 0.74 0.02 0 0.64

30 0 0 0.11 0.11 0.54 0 0.22 0.76 0.02 0 0.64

31 0 0 0.11 0.11 0.58 0 0.23 0.82 0.02 0 0.64

32 0 0 0.11 0.11 0.51 0 0.23 0.74 0.02 0 0.64

340

No CHW_Total CNHW_A1 CHNW_A2 CNHW_A3 CNHW_Total Initial_cost_items

1 0.66 0.19 0 6.67 6.86 123

2 0.67 0.34 0 6.67 7.01 124

3 0.66 0.21 0 6.67 6.87 120

4 0.66 0.21 0 6.67 6.87 120

5 0.66 0.22 0 6.67 6.89 120

6 0.67 0.32 0 6.67 6.99 120

7 0.66 0.17 0 6.67 6.84 120

8 0.66 0.21 0 6.67 6.88 120

9 0.66 0.21 0 6.67 6.87 120

10 0.66 0.19 0 6.67 6.86 123

11 0.66 0.21 0 6.67 6.88 118

12 0.68 0.4 0 6.67 7.07 122

13 0.66 0.19 0 6.67 6.86 123

14 0.66 0.21 0 6.67 6.88 120

15 0.66 0.21 0 6.67 6.88 130

16 0.66 0.19 0 6.67 6.86 112

17 0.66 0.19 0 6.67 6.86 112

18 0.67 0.3 0 6.67 6.97 118

19 0.66 0.23 0 6.67 6.9 112

20 0.66 0.25 0 6.67 6.92 112

21 0.66 0.19 0 6.67 6.86 117

22 0.66 0.19 0 6.67 6.86 117

23 0.66 0.19 0 6.67 6.86 117

24 0.66 0.18 0 6.67 6.85 112

25 0.66 0.19 0 6.67 6.86 112

341

26 0.66 0.21 0 6.67 6.87 122

27 0.66 0.19 0 6.67 6.86 106

28 0.66 0.27 0 6.67 6.94 108

29 0.66 0.19 0 6.67 6.86 120

30 0.66 0.21 0 6.67 6.87 122

31 0.66 0.22 0 6.67 6.89 122

32 0.66 0.18 0 6.67 6.85 122

342

APPENDIX E. INVENTORY VALUES FOR TRUCKS USED IN THE

TRANSPORTATION MODULE

This section presents the inventory values used for the trucks presented in the transportation

module.

Table E1 Transport, single unit truck, diesel powered per (ton.km) data

Details for Transport, single unit truck, diesel powered

Flow Category Flow Type Unit Amount

Outputs

Carbon dioxide, fossil air/unspecified Elementary kg 1.71E-01

Carbon monoxide, fossil air/unspecified Elementary kg 2.46E-04

Methane, fossil air/unspecified Elementary kg 4.13E-06

Nitrogen oxides air/unspecified Elementary kg 1.22E-03

Particulates, < 10 um air/unspecified Elementary kg 2.35E-05

Sulfur oxides air/unspecified Elementary kg 3.77E-05

VOC, volatile organic

compounds air/unspecified Elementary kg 8.42E-05

Table E2 Single unit truck, long-haul, diesel powered per (ton.km) data

Details for Transport, single unit truck, long-haul, diesel powered

Flow Category Flow Type Unit Amount

Outputs

Ammonia air/unspecified Elementary kg 7.84E-06

Carbon dioxide, fossil air/unspecified Elementary kg 3.23E-01

Carbon monoxide, fossil air/unspecified Elementary kg 8.23E-04

Methane air/unspecified Elementary kg 1.00E-05

Nitrogen dioxide air/unspecified Elementary kg 1.77E-04

Nitrogen oxides air/unspecified Elementary kg 1.71E-03

Nitrous oxide air/unspecified Elementary kg 9.31E-07

Particulates, < 10 um air/unspecified Elementary kg 9.10E-05

Particulates, < 10 um air/unspecified Elementary kg 4.19E-06

Particulates, < 10 um air/unspecified Elementary kg 2.10E-05

Particulates, < 2.5 um air/unspecified Elementary kg 5.49E-06

Particulates, < 2.5 um air/unspecified Elementary kg 1.00E-06

Particulates, < 2.5 um air/unspecified Elementary kg 8.82E-05

Sulfur dioxide air/unspecified Elementary kg 5.02E-06

VOC, volatile organic compounds air/unspecified Elementary kg 2.06E-04

Table E3 Combination truck, gasoline powered per (ton.km) data

Details for Transport, combination truck, gasoline powered

Flow Category Flow Type Unit Amount

Outputs

Carbon dioxide, fossil air/unspecified Elementary kg 6.18E-02

343

Carbon monoxide, fossil air/unspecified Elementary kg 1.23E-03

Methane, fossil air/unspecified Elementary kg 8.90E-06

Nitrogen oxides air/unspecified Elementary kg 3.38E-04

Particulates, < 10 um air/unspecified Elementary kg 1.48E-06

Sulfur oxides air/unspecified Elementary kg 1.48E-05

VOC, volatile organic

compounds air/unspecified Elementary kg 5.53E-05

Table E3 Single unit truck, gasoline powered per ( ton.km) data

Details for Transport, single unit truck, gasoline powered

Flow Category Flow Type Unit Amount

Outputs

Carbon dioxide, fossil air/unspecified Elementary kg 1.32E-01

Carbon monoxide,

fossil air/unspecified Elementary kg 2.38E-03

Methane, fossil air/unspecified Elementary kg 2.85E-05

Nitrogen oxides air/unspecified Elementary kg 7.75E-04

Particulates, < 10 um air/unspecified Elementary kg 3.79E-06

Sulfur oxides air/unspecified Elementary kg 3.16E-05

VOC, volatile organic

compounds air/unspecified Elementary kg 1.77E-04

Table E4 Single unit truck, long-haul, gasoline powered per (ton.km) data

Details for Transport, single unit truck, long-haul, gasoline powered

Flow Category Flow Type Unit Amount

Outputs

Ammonia air/unspecified Elementary kg 1.31E-05

Carbon dioxide, fossil air/unspecified Elementary kg 3.11E-01

Carbon monoxide,

fossil air/unspecified Elementary kg 1.01E-02

Methane air/unspecified Elementary kg 1.57E-05

Nitrogen dioxide air/unspecified Elementary kg 9.83E-05

Nitrogen oxides air/unspecified Elementary kg 1.16E-03

Nitrous oxide air/unspecified Elementary kg 1.44E-05

Particulates, < 10 um air/unspecified Elementary kg 4.49E-06

Particulates, < 10 um air/unspecified Elementary kg 3.34E-06

Particulates, < 10 um air/unspecified Elementary kg 1.75E-05

Particulates, < 2.5 um air/unspecified Elementary kg 4.59E-06

Particulates, < 2.5 um air/unspecified Elementary kg 4.14E-06

Particulates, < 2.5 um air/unspecified Elementary kg 8.01E-07

Sulfur dioxide air/unspecified Elementary kg 5.77E-06

VOC, volatile organic

compounds air/unspecified Elementary kg 4.71E-04

344

APPENDIX F. LCCA FOR TEXAS

Age Activity Quantity Unit

Unit

price Total

$ $

Maintenance and repair

15 Diamond grinding existing surface 0 yd2 5.6 0

15 Full depth pavement design 32 yd2 200 6400

15 MOT at 5% 320

15 Design cost at 10% 640

15

Construction inspection services at

10% 640

Total 8000

Major

maintenance

25 Diamond grinding existing surface 22293 yd2 5.6 124840.8

25 Full depth pavement repair 4.8 yd2 200 960

25 MOT at 5% 6290

25 Design cost at 10% 12580

25

Construction inspection services at

10% 12580

25 Total 157250.8

Minor

maintenance

40 Diamond grinding existing surface 0 yd2 5.6 0

40 Full depth pavement repair 4 yd2 200 800

40 MOT at 5% 40

40 Design cost at 10% 80

40

Construction inspection services at

10% 80

Total 1000

Major

rehabilitation

60 Milling 0 yd2 3.5 0

60 Full depth pavement repairs 184 yd2 150 27600

60 Place asphalt tack coat (9 yd2/gal) 2477 gallon 1.7 4210.9

60 2 inch HMA binder 2475 tons 65 160846

60 2 inch HMA surface 2475 tons 65 160846

60 MOT at 5% 17675

345

60 Design cost at 10% 35350

60

Construction inspection services at

10% 35350

Total 441877.9

Salvage value -75,002

Overall Total (all items) 608,129

346

VITA

Neveen Soliman holds a bachelor degree in Construction Engineering and a Master degree in

Environmental Engineering. She joined LSU in 2014 as a graduate student.